DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Receipt is acknowledged of certified copies of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Response to Arguments
Applicant’s arguments see remarks, filed 05/26/2026, with respect to claims 1-39 have been considered but are moot because the arguments do not apply to the current combinations of references being used in the current rejection.
Claim Objections
Claims 8, 12, 20, and 24 are objected to because of the following informalities:
In claim 8, line 4, the term “CIELAB” is objected to because acronyms must be presented with their meanings the first time they are mentioned in the group of claims.
In claim 12, line 2, the term “calibrate the skin analysis assembly” should be changed to “calibrate a skin analysis assembly” in order to avoid an insufficient antecedent issue and prevent a rejection under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph.
In claim 20, line 4, the term “CIELAB” is objected to because acronyms must be presented with their meanings the first time they are mentioned in the group of claims.
In claim 24, line 2, the term “calibrating the skin analysis assembly” should be changed to “calibrating a skin analysis assembly” in order to avoid an insufficient antecedent issue and prevent a rejection under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim 1 along with its dependent claims, claims 2-3, 5-12, and 32-35 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, because the specification, while being enabling for when implemented in software, the software code can be executed on any suitable processor or collection of processors, whether provided in a single computer or distributed among multiple computers. Also, the various methods or processes outlined herein may be coded as software that is executable on one or more processors that employ any one of a variety of operating systems or platforms, as described in Paragraph [0047-0048] in the specification, does not reasonably provide enablement for explicitly disclosing the claim language “a processing system comprising one or more processors”, as claimed in claim 1.
The specification does not enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to use the invention commensurate in scope with these claims. The claimed subject matter, not taught by the specification is a processing system comprising one or more processors. No where in the specification is the term “processing system,” or the like, mentioned.
Claim 13 along with its dependent claims, claims 14-15, 17-24, and 36-39, are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, because the specification, while being enabling for when implemented in software, the software code can be executed on any suitable processor or collection of processors, whether provided in a single computer or distributed among multiple computers. Also, the various methods or processes outlined herein may be coded as software that is executable on one or more processors that employ any one of a variety of operating systems or platforms, as described in Paragraph [0047-0048] in the specification, does not reasonably provide enablement for explicitly disclosing the claim language “a processing system” and “one or more processors of the processing system”, as claimed in claim 13.
The specification does not enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to use the invention commensurate in scope with these claims. The claimed subject matter, not taught by the specification is “a processing system” and “one or more processors of the processing system”. No where in the specification is the term “processing system,” or the like, mentioned.
Claims 12 and 24 along with their dependent claims are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, because the specification, while being enabling for by way of example, one approach, that is considered desirable and accurate, is to use a spectrophotometer. Such a device does not use a camera and image analysis but rather uses wavelengths of light reflected to a sensor to determine a color of the subject (for example of a user's face). Such devices are expensive and are known to be effective for solid homogeneous colors, but not for non-homogeneous colors. Notably, and as mentioned, system 100 requires the ability to obtain skin images that allow the processing described herein. In one embodiment, skin images may be taken using cross polarized light (for example to remove glare, or reflection of the light source from the skin image), with a 10 megapixel camera at a magnification of not less than 10x, as described in Paragraph [004 and 0020] in the specification, does not reasonably provide enablement for explicitly disclosing the claim language “calibrating the skin analysis assembly, by taking one or more images of a calibration card using a camera of the processing system,” as claimed in claim 1.
The specification does not enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to use the invention commensurate in scope with these claims. The claimed subject matter, not taught by the specification is “calibrating the skin analysis assembly, by taking one or more images of a calibration card using a camera of the processing system.”
The office respectfully requests the Applicant to indicate where in the specification teaches the limitation in claims 1, 12-13, 24, and their dependent claims, or amend in order to overcome the rejection under 35 U.S.C. 112(a.).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over LEWIS et al. (US 20140341442 A1), hereinafter referenced as LEWIS, in view of HARVILLE et al. (US 20070058858 A1), hereinafter referenced as HARVILLE.
Regarding claim 1, LEWIS explicitly teaches a system for user skin color determination of a user (Fig. 3. Paragraph [0053]-LEWIS discloses the method determines a characteristic skin color for the selected face region pixels.), the system comprising:
a processing system comprising one or more processors (Fig. 2. Paragraph [0026]-LEWIS discloses the system includes one or more processors or processing circuitry.), configured to:
obtain a user skin image of the user, comprising a plurality of user skin image pixels (Fig. 6. Paragraph [0017]-LEWIS discloses the system determines a face image mask for the image that indicates which pixels in the image are skin pixels depicting the person's skin. The system can determine the skin pixels based on a threshold similarity in color to the characteristic skin color.);
perform color processing on the user skin image to arrive at a user skin color (Fig. 3. Paragraph [0017]-LEWIS discloses the pixel colors can be converted to a particular color space and checked as to which ones have colors included in a predetermined range of the color space indicative of known skin tones. A characteristic skin color is determined for the selected pixels having colors in the predetermined range, such as by averaging the colors.), comprising:
determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image (Fig. 3. Paragraph [0017]-LEWIS discloses a characteristic skin color is determined for the selected pixels having colors in the predetermined range, such as by averaging the colors (wherein the averaged colors is the condition color score).);
calculating a per-pixel condition color threshold (Fig. 3. Paragraph [0059]-LEWIS discloses the threshold range is based on the distribution of colors of the pixels selected to determine the characteristic color in block 308. For example, the standard deviation of each color channel as determined in block 310 can be used as an indication of how wide is the color distribution in a channel, and the threshold range can be based on the standard deviation.);
generating a condition color mask based on the per-pixel condition color threshold (Fig. 3. Paragraph [0059]-LEWIS discloses in block 318 the method designates particular mask pixels of the face mask to indicate facial skin pixels in the image. The designated mask pixels are those pixels corresponding to image pixels having a color within a threshold similarity to the characteristic skin color.); and
calculating a user skin color from the plurality of user skin image pixels (Fig. 3. Paragraph [0053]-LEWIS discloses the method determines a characteristic skin color for the selected face region pixels. For example, in some implementations, the characteristic skin color is the average color of the selected face region pixels, e.g., the average color component in each of the three R, G, and B color channels for the selected pixels.); and
LEWIS fails to explicitly teach when the average pixel condition color score is below an image condition color threshold, then: removing pixels, from the plurality of user skin image pixels, that exceed the per-pixel condition color threshold; and output a result of the color processing, the result comprising the user skin color.
However, HARVILLE explicitly teaches when the average pixel condition color score is below an image condition color threshold, then (Fig. 4A. Paragraph [0068]-HARVILLE discloses the luminance (Y) of a pixel may be computed using the following formula: Y=R+G+B where R, G, and B are the red, green, and blue component values of the pixel. Having computed the luminance of each pixel, skin pixel selection component 402 sorts the pixels in order of increasing luminance. Skin pixel selection component 402 then eliminates skin pixels that have a luminance below a lower threshold or above an upper threshold (wherein luminance is the average pixel condition color score).):
removing pixels, from the plurality of user skin image pixels, that exceed the per-pixel condition color threshold (Fig. 4A. Paragraph [0068]-HARVILLE discloses skin pixel selection component 402 then eliminates skin pixels that have a luminance below a lower threshold or above an upper threshold.); and
output a result of the color processing (Fig. 4A, illustrates outputting a result of color processing in block #413 called Skin Color Estimate.), the result comprising the user skin color (Fig. 4A. Paragraph [0056]-HARVILLE discloses a modified color value 209 is output to skin color estimator 403 which generates a skin color estimate 413 based thereon.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of HARVILLE of when the average pixel condition color score is below an image condition color threshold, then: removing pixels, from the plurality of user skin image pixels, that exceed the per-pixel condition color threshold; and output a result of the color processing, the result comprising the user skin color.
Wherein having LEWIS’s system for determining skin color having when the average pixel condition color score is below an image condition color threshold, then: removing pixels, from the plurality of user skin image pixels, that exceed the per-pixel condition color threshold; and output a result of the color processing, the result comprising the user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and HARVILLE relate to detecting and analyzing skin in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while HARVILLE the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and HARVILLE et al. (US 20070058858 A1), Paragraph [0005].
Regarding claim 13, LEWIS explicitly teaches a method for user skin color determination of a user (Fig. 3. Paragraph [0053]-LEWIS discloses the method determines a characteristic skin color for the selected face region pixels.), the method comprising:
obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels (Fig. 6. Paragraph [0017]-LEWIS discloses the system determines a face image mask for the image that indicates which pixels in the image are skin pixels depicting the person's skin. The system can determine the skin pixels based on a threshold similarity in color to the characteristic skin color.);
performing, by one or more processors of the processing system (Fig. 2. Paragraph [0026]-LEWIS discloses the system includes one or more processors or processing circuitry.), color processing on the user skin image to arrive at a user skin color (Fig. 3. Paragraph [0017]-LEWIS discloses the pixel colors can be converted to a particular color space and checked as to which ones have colors included in a predetermined range of the color space indicative of known skin tones. A characteristic skin color is determined for the selected pixels having colors in the predetermined range, such as by averaging the colors.), comprising:
determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image (Fig. 3. Paragraph [0017]-LEWIS discloses a characteristic skin color is determined for the selected pixels having colors in the predetermined range, such as by averaging the colors (wherein the averaged colors is the condition color score).);
calculating a per-pixel condition color threshold (Fig. 3. Paragraph [0059]-LEWIS discloses the threshold range is based on the distribution of colors of the pixels selected to determine the characteristic color in block 308. For example, the standard deviation of each color channel as determined in block 310 can be used as an indication of how wide is the color distribution in a channel, and the threshold range can be based on the standard deviation.);
generating a condition color mask based on the per-pixel condition color threshold (Fig. 3. Paragraph [0059]-LEWIS discloses in block 318 the method designates particular mask pixels of the face mask to indicate facial skin pixels in the image. The designated mask pixels are those pixels corresponding to image pixels having a color within a threshold similarity to the characteristic skin color.); and
calculating a user skin color from the plurality of user skin image pixels (Fig. 3. Paragraph [0053]-LEWIS discloses the method determines a characteristic skin color for the selected face region pixels. For example, in some implementations, the characteristic skin color is the average color of the selected face region pixels, e.g., the average color component in each of the three R, G, and B color channels for the selected pixels.); and
LEWIS fails to explicitly teach when the average pixel condition color score is below an image condition color threshold, then: removing pixels, from the plurality of user skin image pixels, that exceed the per-pixel condition color threshold; and outputting, by the processing system, a result of the color processing, the result comprising the user skin color.
However, HARVILLE explicitly teaches when the average pixel condition color score is below an image condition color threshold, then (Fig. 4A. Paragraph [0068]-HARVILLE discloses the luminance (Y) of a pixel may be computed using the following formula: Y=R+G+B where R, G, and B are the red, green, and blue component values of the pixel. Having computed the luminance of each pixel, skin pixel selection component 402 sorts the pixels in order of increasing luminance. Skin pixel selection component 402 then eliminates skin pixels that have a luminance below a lower threshold or above an upper threshold (wherein luminance is the average pixel condition color score).):
removing pixels, from the plurality of user skin image pixels, that exceed the per-pixel condition color threshold (Fig. 4A. Paragraph [0068]-HARVILLE discloses skin pixel selection component 402 then eliminates skin pixels that have a luminance below a lower threshold or above an upper threshold.); and
outputting, by the processing system, a result of the color processing (Fig. 4A, illustrates outputting a result of color processing in block #413 called Skin Color Estimate.), the result comprising the user skin color (Fig. 4A. Paragraph [0056]-HARVILLE discloses a modified color value 209 is output to skin color estimator 403 which generates a skin color estimate 413 based thereon.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of HARVILLE of when the average pixel condition color score is below an image condition color threshold, then: removing pixels, from the plurality of user skin image pixels, that exceed the per-pixel condition color threshold; and outputting, by the processing system, a result of the color processing, the result comprising the user skin color.
Wherein having LEWIS’s system for determining skin color having when the average pixel condition color score is below an image condition color threshold, then: removing pixels, from the plurality of user skin image pixels, that exceed the per-pixel condition color threshold; and outputting, by the processing system, a result of the color processing, the result comprising the user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and HARVILLE relate to detecting and analyzing skin in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while HARVILLE the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and HARVILLE et al. (US 20070058858 A1), Paragraph [0005].
Claims 2-3 and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over LEWIS et al. (US 20140341442 A1), hereinafter referenced as LEWIS, in view of HARVILLE et al. (US 20070058858 A1), hereinafter referenced as HARVILLE, and further in view of RATTNER et al. (US 20190125249 A1), hereinafter referenced as RATTNER.
Regarding claim 2, LEWIS in view of HARVILLE explicitly teach the system of claim 1,
LEWIS in view of HARVILLE fail to explicitly teach wherein the processing system comprises a skin analysis device attached to a mobile device.
However, RATTNER explicitly teaches wherein the processing system comprises a skin analysis device attached to a mobile device (Fig. 1. Paragraph [0218]-RATTNER discloses electronic device: a device, having a camera, onto which a skin analysis device can be attached, that may preferably be mobile (such as mobile phones and tablets), exemplary electronic devices including smart phones, tablets, digital cameras, personal computers, televisions and the like.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of RATTNER of wherein the processing system comprises a skin analysis device attached to a mobile device.
Wherein having LEWIS’s system for determining skin color wherein the processing system comprises a skin analysis device attached to a mobile device.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and RATTNER relate to analyzing skin images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while RATTNER a need in the art for an improved method and system capable of skin analysis using electronic devices such as smartphones. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and RATTNER et al. (US 20190125249 A1), Paragraph [0009].
Regarding claim 3, LEWIS in view of HARVILLE and further in view of RATTNER explicitly teach the system of claim 2,
LEWIS in view of HARVILLE fail to explicitly teach wherein the user skin image is at a magnification of not less than 10x.
However, RATTNER explicitly teaches wherein the user skin image is at a magnification of not less than 10x (Fig. 1. Paragraph [0270]-RATTNER discloses lens 34 may be a magnification lens that has a magnification factor as appropriate for the skin surface being imaged (for example a 30× lens 34 for skin analysis and a different magnification for hair analysis).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of RATTNER of wherein the user skin image is at a magnification of not less than 10x.
Wherein having LEWIS’s system for determining skin color wherein the user skin image is at a magnification of not less than 10x.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and RATTNER relate to analyzing skin images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while RATTNER a need in the art for an improved method and system capable of skin analysis using electronic devices such as smartphones. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and RATTNER et al. (US 20190125249 A1), Paragraph [0009].
Regarding claim 14, LEWIS in view of HARVILLE explicitly teach the method of claim 13,
LEWIS in view of HARVILLE fail to explicitly teach wherein the processing system comprises a skin analysis device attached to a mobile device.
However, RATTNER explicitly teaches wherein the processing system comprises a skin analysis device attached to a mobile device (Fig. 1. Paragraph [0218]-RATTNER discloses electronic device: a device, having a camera, onto which a skin analysis device can be attached, that may preferably be mobile (such as mobile phones and tablets), exemplary electronic devices including smart phones, tablets, digital cameras, personal computers, televisions and the like.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of RATTNER of wherein the processing system comprises a skin analysis device attached to a mobile device.
Wherein having LEWIS’s system for determining skin color wherein the processing system comprises a skin analysis device attached to a mobile device.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and RATTNER relate to analyzing skin images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while RATTNER a need in the art for an improved method and system capable of skin analysis using electronic devices such as smartphones. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and RATTNER et al. (US 20190125249 A1), Paragraph [0009].
Regarding claim 15, LEWIS in view of HARVILLE and further in view of RATTNER explicitly teach the method of claim 14,
LEWIS in view of HARVILLE fail to explicitly teach wherein the user skin image is at a magnification of not less than 10x.
However, RATTNER explicitly teaches wherein the user skin image is at a magnification of not less than 10x (Fig. 1. Paragraph [0270]-RATTNER discloses lens 34 may be a magnification lens that has a magnification factor as appropriate for the skin surface being imaged (for example a 30× lens 34 for skin analysis and a different magnification for hair analysis).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of RATTNER of wherein the user skin image is at a magnification of not less than 10x.
Wherein having LEWIS’s system for determining skin color wherein the user skin image is at a magnification of not less than 10x.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and RATTNER relate to analyzing skin images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while RATTNER a need in the art for an improved method and system capable of skin analysis using electronic devices such as smartphones. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and RATTNER et al. (US 20190125249 A1), Paragraph [0009].
Claims 5 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over LEWIS et al. (US 20140341442 A1), hereinafter referenced as LEWIS, in view of HARVILLE et al. (US 20070058858 A1), hereinafter referenced as HARVILLE, and further in view YUAN et al. (US 20120301024 A1), hereinafter referenced as YUAN.
Regarding claim 5, LEWIS in view of HARVILLE explicitly teach the system of claim 1,
LEWIS fails to explicitly teach wherein the average pixel condition color score comprises an average pixel redness score.
However, HARVILLE explicitly teaches wherein the average pixel condition color score comprises an average pixel redness score (Fig. 5. Paragraph [0068]-HARVILLE discloses the luminance (Y) of a pixel may be computed using the following formula: Y=R+G+B where R, G, and B are the red, green, and blue component values of the pixel (wherein the red component value is the average pixel redness score).);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of HARVILLE of wherein the average pixel condition color score comprises an average pixel redness score.
Wherein having LEWIS’s system for determining skin color wherein the average pixel condition color score comprises an average pixel redness score.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and HARVILLE relate to detecting and analyzing skin in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while HARVILLE the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and HARVILLE et al. (US 20070058858 A1), Paragraph [0005].
LEWIS in view of HARVILLE fail to explicitly teach the image condition color threshold comprises an image redness threshold; the per-pixel condition color threshold comprises a per-pixel redness threshold; and the condition color mask comprises a redness mask.
However, YUAN explicitly teaches the image condition color threshold comprises an image redness threshold (Fig. 2. Paragraph [0038]-YUAN discloses the redness threshold may be expressed as: {square root over ((2.5*variance)+mean)}, in which variance is the variance of the redness measures of the pixels in the larger strong red eye area that are included by the redness value, and mean is the mean of the redness measures of the pixels in the larger strong red eye area that are include by the redness value.);
the per-pixel condition color threshold comprises a per-pixel redness threshold (Fig. 2. Paragraph [0038]-YUAN discloses the redness threshold may be expressed as: {square root over ((2.5*variance)+mean)}, in which variance is the variance of the redness measures of the pixels in the larger strong red eye area that are included by the redness value, and mean is the mean of the redness measures of the pixels in the larger strong red eye area that are include by the redness value.); and
the condition color mask comprises a redness mask (Fig. 2. Paragraph [0028]-YUAN discloses a red eye area pixel may be labeled with a binary value of "1", while a background pixel may be labeled with a binary value of "0". In this example, the detection module 212 may construct a binary mask that encompasses the one or more candidate red eye areas by discarding pixels that are labeled with "0" (wherein the binary mask is a redness mask).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of YUAN of the image condition color threshold comprises an image redness threshold; the per-pixel condition color threshold comprises a per-pixel redness threshold; and the condition color mask comprises a redness mask.
Wherein having LEWIS’s system for determining skin color having the image condition color threshold comprises an image redness threshold; the per-pixel condition color threshold comprises a per-pixel redness threshold; and the condition color mask comprises a redness mask.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and YUAN relate to analyzing pictures of humans and identifying colors, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while YUAN the desired correction of the redness in each pixel of the correction region is achieved. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and YUAN et al. (US 20120301024 A1), Paragraph [0024].
Regarding claim 17, LEWIS in view of HARVILLE explicitly teach the method of claim 13,
LEWIS fails to explicitly teach wherein: the average pixel condition color score comprises an average pixel redness score.
However, HARVILLE explicitly teaches wherein: the average pixel condition color score comprises an average pixel redness score (Fig. 5. Paragraph [0068]-HARVILLE discloses the luminance (Y) of a pixel may be computed using the following formula: Y=R+G+B where R, G, and B are the red, green, and blue component values of the pixel (wherein the red component value is the average pixel redness score).);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of HARVILLE of wherein: the average pixel condition color score comprises an average pixel redness score.
Wherein having LEWIS’s system for determining skin color having wherein: the average pixel condition color score comprises an average pixel redness score.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and HARVILLE relate to detecting and analyzing skin in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while HARVILLE the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and HARVILLE et al. (US 20070058858 A1), Paragraph [0005].
LEWIS in view of HARVILLE fail to explicitly teach the image condition color threshold comprises an image redness threshold; the per-pixel condition color threshold comprises a per-pixel redness threshold; and the condition color mask comprises a redness mask.
However, YUAN explicitly teaches the image condition color threshold comprises an image redness threshold (Fig. 2. Paragraph [0038]-YUAN discloses the redness threshold may be expressed as: {square root over ((2.5*variance)+mean)}, in which variance is the variance of the redness measures of the pixels in the larger strong red eye area that are included by the redness value, and mean is the mean of the redness measures of the pixels in the larger strong red eye area that are include by the redness value.);
the per-pixel condition color threshold comprises a per-pixel redness threshold (Fig. 2. Paragraph [0038]-YUAN discloses the redness threshold may be expressed as: {square root over ((2.5*variance)+mean)}, in which variance is the variance of the redness measures of the pixels in the larger strong red eye area that are included by the redness value, and mean is the mean of the redness measures of the pixels in the larger strong red eye area that are include by the redness value.); and
the condition color mask comprises a redness mask (Fig. 2. Paragraph [0028]-YUAN discloses a red eye area pixel may be labeled with a binary value of "1", while a background pixel may be labeled with a binary value of "0". In this example, the detection module 212 may construct a binary mask that encompasses the one or more candidate red eye areas by discarding pixels that are labeled with "0" (wherein the binary mask is a redness mask).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of YUAN of the image condition color threshold comprises an image redness threshold; the per-pixel condition color threshold comprises a per-pixel redness threshold; and the condition color mask comprises a redness mask.
Wherein having LEWIS’s system for determining skin color having the image condition color threshold comprises an image redness threshold; the per-pixel condition color threshold comprises a per-pixel redness threshold; and the condition color mask comprises a redness mask.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and YUAN relate to analyzing pictures of humans and identifying colors, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while YUAN the desired correction of the redness in each pixel of the correction region is achieved. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and YUAN et al. (US 20120301024 A1), Paragraph [0024].
Claims 6 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over LEWIS et al. (US 20140341442 A1), hereinafter referenced as LEWIS, in view of HARVILLE et al. (US 20070058858 A1), hereinafter referenced as HARVILLE, and further in view LEE et al. (US 20210279547 A1), hereinafter referenced as LEE.
Regarding claim 6, LEWIS in view of HARVILLE explicitly teach the system of claim 1,
LEWIS in view of HARVILLE fail to explicitly teach wherein the determining further comprises using a human perception mimicking algorithm developed using empirical A/B testing results.
However, LEE explicitly teaches wherein the determining further comprises using a human perception mimicking algorithm developed using empirical A/B testing results (Fig. 2. Paragraph [0133]-LEE discloses this is the first attempt to formally test the possibility that computational models mimicking the way the brain solves general problems can lead to practical solutions to key challenges in machine learning.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of LEE of wherein the determining further comprises using a human perception mimicking algorithm developed using empirical A/B testing results.
Wherein having LEWIS’s system for determining skin color wherein the determining further comprises using a human perception mimicking algorithm developed using empirical A/B testing results.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and LEE relate to computers receiving human input, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while LEE humans' RL enables minimal supervision learning. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and LEE et al. (US 20210279547 A1), Paragraph [0098].
Regarding claim 18, LEWIS in view of HARVILLE explicitly teach the method of claim 13,
LEWIS in view of HARVILLE fail to explicitly teach wherein the determining further comprises using a human perception mimicking algorithm developed using empirical A/B testing results.
However, LEE explicitly teaches wherein the determining further comprises using a human perception mimicking algorithm developed using empirical A/B testing results (Fig. 2. Paragraph [0133]-LEE discloses this is the first attempt to formally test the possibility that computational models mimicking the way the brain solves general problems can lead to practical solutions to key challenges in machine learning.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of LEE of wherein the determining further comprises using a human perception mimicking algorithm developed using empirical A/B testing results.
Wherein having LEWIS’s system for determining skin color wherein the determining further comprises using a human perception mimicking algorithm developed using empirical A/B testing results.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and LEE relate to computers receiving human input, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while LEE humans' RL enables minimal supervision learning. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and LEE et al. (US 20210279547 A1), Paragraph [0098].
Claims 7 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over LEWIS et al. (US 20140341442 A1), hereinafter referenced as LEWIS, in view of HARVILLE et al. (US 20070058858 A1), hereinafter referenced as HARVILLE, and further in view YUAN et al. (US 20120301024 A1), hereinafter referenced as YUAN, and further in view of MACKINNON et al. (WO 2019144247 A1), hereinafter referenced as MACKINNON.
Regarding claim 7, LEWIS in view of HARVILLE and further in view of YUAN explicitly teaches the system of claim 5,
Although YUAN explicitly teaches wherein the image redness threshold, LEWIS in view of HARVILLE and further in view of YUAN fail to explicitly teach wherein the image redness threshold is based on one or more of a processing power of the system, a desired speed and a desired accuracy of the user skin color.
However, MACKINNON explicitly teaches wherein the image redness threshold (Fig. 7. Paragraph [0011]-MACKINNON discloses digital color images can be based on color or gray scale thresholding, using RGB image data, or using other color spaces such as YCR or CIE 1976 L*a*b* color space and some kind of feature recognition and classification algorithm. Further in paragraph [0050-0051]-MACKINNON discloses the difference between the a* image before and after smoothing is used to find the redness change in each pixel [620] Pixels with large differences in redness are then considered as an acne (Otsu thresholding) and used to create a binary image of acne lesions [630] FIG. 7 shows an exemplary RGB image exhibiting a user-captured image [700], a* image before [710] and after Gaussian filter implementation [720], difference of redness [730], and generated binary image of acne lesions [740]) is based on one or more of a processing power of the system, a desired speed, and a desired accuracy of the user skin color (Fig. 7. Paragraph [0041]-MACKINNON discloses the processing software may be installed on the mobile device. At this time, the processing capability of mobile devices is insufficient to provide sufficient processing capability for some applications. For those applications where the processing capability of the mobile device is sufficient, data processing may occur on the mobile device. In some embodiments, the system and method comprises capturing images of the face using the mobile application on the smart phone and uploading the images to a cloud server for storage and processing.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE and further in view of YUAN of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of MACKINNON of wherein the image redness threshold is based on one or more of a processing power of the system, a desired speed and a desired accuracy of the user skin color.
Wherein having LEWIS’s system for determining skin color wherein the image redness threshold is based on one or more of a processing power of the system, a desired speed and a desired accuracy of the user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and MACKINNON relate to analyzing skin images of a person, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while MACKINNON it is a goal of this invention to overcome existing difficulties in observing the evolution of acne over time without the need for face and head positioning fixtures and complex imaging devices that require deployment in a clinical or laboratory setting and to provide individuals who may be suffering from chronic acne with digital tools to assess and monitor the progress of their disease using their smart phone or tablet as a mobile medical device. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and MACKINNON et al. (WO 2019144247 A1), Paragraph [0013].
Regarding claim 19, LEWIS in view of HARVILLE and further in view of YUAN the method of claim 17,
Although YUAN explicitly teaches wherein the image redness threshold, LEWIS in view of HARVILLE and further in view of YUAN fail to explicitly teach wherein the image redness threshold is based on one or more of a processing power of the system, a desired speed and a desired accuracy of the user skin color.
However, MACKINNON explicitly teaches wherein the image redness threshold (Fig. 7. Paragraph [0011]-MACKINNON discloses digital color images can be based on color or gray scale thresholding, using RGB image data, or using other color spaces such as YCR or CIE 1976 L*a*b* color space and some kind of feature recognition and classification algorithm. Further in paragraph [0050-0051]-MACKINNON discloses the difference between the a* image before and after smoothing is used to find the redness change in each pixel [620] Pixels with large differences in redness are then considered as an acne (Otsu thresholding) and used to create a binary image of acne lesions [630] FIG. 7 shows an exemplary RGB image exhibiting a user-captured image [700], a* image before [710] and after Gaussian filter implementation [720], difference of redness [730], and generated binary image of acne lesions [740]) is based on one or more of a processing power of the system, a desired speed, and a desired accuracy of the user skin color (Fig. 7. Paragraph [0041]-MACKINNON discloses the processing software may be installed on the mobile device. At this time, the processing capability of mobile devices is insufficient to provide sufficient processing capability for some applications. For those applications where the processing capability of the mobile device is sufficient, data processing may occur on the mobile device. In some embodiments, the system and method comprises capturing images of the face using the mobile application on the smart phone and uploading the images to a cloud server for storage and processing.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE and further in view of YUAN of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of MACKINNON of wherein the image redness threshold is based on one or more of a processing power of the system, a desired speed and a desired accuracy of the user skin color.
Wherein having LEWIS’s system for determining skin color wherein the image redness threshold is based on one or more of a processing power of the system, a desired speed and a desired accuracy of the user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and MACKINNON relate to analyzing skin images of a person, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while MACKINNON it is a goal of this invention to overcome existing difficulties in observing the evolution of acne over time without the need for face and head positioning fixtures and complex imaging devices that require deployment in a clinical or laboratory setting and to provide individuals who may be suffering from chronic acne with digital tools to assess and monitor the progress of their disease using their smart phone or tablet as a mobile medical device. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and MACKINNON et al. (WO 2019144247 A1), Paragraph [0013].
Claims 9-12, 21-24, 35, and 39 are rejected under 35 U.S.C. 103 as being unpatentable over LEWIS et al. (US 20140341442 A1), hereinafter referenced as LEWIS, in view of HARVILLE et al. (US 20070058858 A1), hereinafter referenced as HARVILLE, and further in view BHATTI et al. (US 20070071314 A1), hereinafter referenced as BHATTI.
Regarding claim 9, LEWIS in view of HARVILLE explicitly teach the system of claim 1, wherein the system is further configured to:
LEWIS in view of HARVILLE fail to explicitly teach apply a color transposition to the user skin color, based on a transposition between the system and an alternative skin color system, and wherein the result further comprises a transposed user skin color.
However, BHATTI explicitly teaches apply a color transposition to the user skin color (Fig. 2. Paragraph [0035]-BHATTI discloses image analysis system 205 is for generating a skin color estimate 413 of subject 203 based upon an analysis of image 202. Further in Paragraph [0036]-BHATTI discloses image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.), based on a transposition between the system and an alternative skin color system (Fig. 2. Paragraph [0036]-BHATTI discloses image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.), and
wherein the result further comprises a transposed user skin color (Fig. 2. Paragraph [0042]-BHATTI discloses the determined color correction function is applied to the color description of one or more of the selected skin pixels located in the image.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of BHATTI of wherein the determining further comprises using a human perception mimicking algorithm developed using empirical A/B testing results.
Wherein having LEWIS’s system for determining skin color wherein the determining further comprises using a human perception mimicking algorithm developed using empirical A/B testing results.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and BHATTI relate to skin analysis systems, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while BHATTI the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and BHATTI et al. (US 20070071314 A1), Paragraph [0007].
Regarding claim 10, LEWIS in view of HARVILLE explicitly teach the system of claim 9, wherein the system is further configured to:
LEWIS fails to explicitly teach provide a product recommendation, based on one or more of the user skin color and the transposed user skin color, and wherein the result further comprises the product recommendation.
However, HARVILLE explicitly teaches provide a product recommendation (Fig. 1. Paragraph [0024]-HARVILLE discloses in step 140 of FIG. 1, at least one product which corresponds with the classification color is recommended. In embodiments of the present invention, a result is generated in which at least one product is recommended to a user.), based on one or more of the user skin color (Fig. 2. Paragraph [0044]-HARVILLE discloses product recommendation system 220 uses the skin color estimate 413 to map subject 203 to a particular bin or plurality of bins based upon the coloration of the subject.), and wherein the result further comprises the product recommendation (Fig. 1. Paragraph [0024]-HARVILLE discloses in step 140 of FIG. 1, at least one product which corresponds with the classification color is recommended. In embodiments of the present invention, a result is generated in which at least one product is recommended to a user.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of HARVILLE of wherein the average pixel condition color score comprises an average pixel redness score.
Wherein having LEWIS’s system for determining skin color wherein the average pixel condition color score comprises an average pixel redness score.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and HARVILLE relate to detecting and analyzing skin in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while HARVILLE the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and HARVILLE et al. (US 20070058858 A1), Paragraph [0005].
LEWIS in view of HARVILLE fails to explicitly teach the transposed user skin color.
However, BHATTI explicitly teaches the transposed user skin color (Fig. 2. Paragraph [0036]-BHATTI discloses image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of BHATTI of the transposed user skin color.
Wherein having LEWIS’s system for determining skin color having the transposed user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and BHATTI relate to skin analysis systems, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while BHATTI the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and BHATTI et al. (US 20070071314 A1), Paragraph [0007].
Regarding claim 11, LEWIS in view of HARVILLE and further in view of BHATTI explicitly teach the system of claim 10, wherein the system is further configured to:
LEWIS fails to explicitly teach receive an empirical feedback, based on one or more of the product recommendation, the user skin color, and the transposed user skin color.
However, HARVILLE explicitly teaches receive an empirical feedback (Fig. 2. Paragraph [0045]-HARVILLE discloses subject 203 can identify additional parameters using, for example, a web interface. These parameters can be used by product recommendation system 220 to further identify the product(s) in which the user is interested. For example, users can indicate that they are interested in clothing, hair coloring, makeup, etc. The users may further indicate specific product groups in which they are interested such as eye makeup, foundation, lipstick, etc. Demographic information may also be collected to further refine a product consultation (wherein the additional parameters are feedback).), based on one or more of the product recommendation (Fig. 1. Paragraph [0024]-HARVILLE discloses in step 140 of FIG. 1, at least one product which corresponds with the classification color is recommended. In embodiments of the present invention, a result is generated in which at least one product is recommended to a user.), the user skin color (Fig. 2. Paragraph [0044]-HARVILLE discloses product recommendation system 220 uses the skin color estimate 413 to map subject 203 to a particular bin or plurality of bins based upon the coloration of the subject.),
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of HARVILLE of wherein the average pixel condition color score comprises an average pixel redness score.
Wherein having LEWIS’s system for determining skin color wherein the average pixel condition color score comprises an average pixel redness score.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and HARVILLE relate to detecting and analyzing skin in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while HARVILLE the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and HARVILLE et al. (US 20070058858 A1), Paragraph [0005].
LEWIS in view of HARVILLE fails to explicitly teach the transposed user skin color.
However, BHATTI explicitly teaches the transposed user skin color (Fig. 2. Paragraph [0036]-BHATTI discloses image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of BHATTI of the transposed user skin color.
Wherein having LEWIS’s system for determining skin color having the transposed user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and BHATTI relate to skin analysis systems, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while BHATTI the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and BHATTI et al. (US 20070071314 A1), Paragraph [0007].
Regarding claim 12, LEWIS in view of HARVILLE explicitly teach the system of claim 1, wherein the system is further configured to:
LEWIS in view of HARVILLE fail to explicitly teach calibrate the skin analysis assembly, by taking one or more images of a calibration card using a camera of the processing system, to obtain a calibration transposition that is applied to the user skin image.
However, BHATTI explicitly teaches calibrate the skin analysis assembly (Fig. 2. Paragraph [0036]-BHATTI discloses by comparing the characteristics of control reference color set 208 with the characteristics of the reference color set 204 captured in the image, image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.), by taking one or more images of a calibration card (Fig. 2. Paragraph [0034]-BHATTI discloses system 200 comprises an image capture device 201 for capturing an image 202 comprising a subject (e.g., 203) and a imaged reference color set 204 (wherein the imaged reference color set is a calibration card).), to obtain a calibration transposition that is applied to the user skin image (Fig. 2. Paragraph [0036]-BHATTI discloses image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of BHATTI of the transposed user skin color.
Wherein having LEWIS’s system for determining skin color having the transposed user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and BHATTI relate to skin analysis systems, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while BHATTI the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and BHATTI et al. (US 20070071314 A1), Paragraph [0007].
Regarding claim 21, LEWIS in view of HARVILLE explicitly teach the method of claim 13, the method further comprising:
LEWIS in view of HARVILLE fail to explicitly teach applying a color transposition to the user skin color, based on a transposition between the system and an alternative skin color system, and wherein the result further comprises a transposed user skin color.
However, BHATTI explicitly teaches applying a color transposition to the user skin color (Fig. 2. Paragraph [0035]-BHATTI discloses image analysis system 205 is for generating a skin color estimate 413 of subject 203 based upon an analysis of image 202. Further in Paragraph [0036]-BHATTI discloses image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.), based on a transposition between the system and an alternative skin color system (Fig. 2. Paragraph [0036]-BHATTI discloses image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.), and
wherein the result further comprises a transposed user skin color (Fig. 2. Paragraph [0042]-BHATTI discloses the determined color correction function is applied to the color description of one or more of the selected skin pixels located in the image.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of BHATTI of applying a color transposition to the user skin color, based on a transposition between the system and an alternative skin color system, and wherein the result further comprises a transposed user skin color.
Wherein having LEWIS’s system for determining skin color having applying a color transposition to the user skin color, based on a transposition between the system and an alternative skin color system, and wherein the result further comprises a transposed user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and BHATTI relate to skin analysis systems, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while BHATTI the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and BHATTI et al. (US 20070071314 A1), Paragraph [0007].
Regarding claim 22, LEWIS in view of HARVILLE and further in view of BHATTI explicitly teach the method of claim 21, the method further comprising:
LEWIS fails to explicitly teaches providing a product recommendation, based on one or more of the user skin color and the transposed user skin color, and wherein the result further comprises the product recommendation.
However, HARVILLE explicitly teaches providing a product recommendation (Fig. 1. Paragraph [0024]-HARVILLE discloses in step 140 of FIG. 1, at least one product which corresponds with the classification color is recommended. In embodiments of the present invention, a result is generated in which at least one product is recommended to a user.), based on one or more of the user skin color (Fig. 2. Paragraph [0044]-HARVILLE discloses product recommendation system 220 uses the skin color estimate 413 to map subject 203 to a particular bin or plurality of bins based upon the coloration of the subject.), and wherein the result further comprises the product recommendation (Fig. 1. Paragraph [0024]-HARVILLE discloses in step 140 of FIG. 1, at least one product which corresponds with the classification color is recommended. In embodiments of the present invention, a result is generated in which at least one product is recommended to a user.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of HARVILLE of providing a product recommendation, based on one or more of the user skin color and the transposed user skin color, and wherein the result further comprises the product recommendation.
Wherein having LEWIS’s system for determining skin color having providing a product recommendation, based on one or more of the user skin color and the transposed user skin color, and wherein the result further comprises the product recommendation.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and HARVILLE relate to detecting and analyzing skin in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while HARVILLE the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and HARVILLE et al. (US 20070058858 A1), Paragraph [0005].
LEWIS in view of HARVILLE fail to explicitly teach and the transposed user skin color.
However, BHATTI explicitly teaches and the transposed user skin color (Fig. 2. Paragraph [0036]-BHATTI discloses image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of BHATTI of and the transposed user skin color.
Wherein having LEWIS’s system for determining skin color having and the transposed user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and BHATTI relate to skin analysis systems, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while BHATTI the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and BHATTI et al. (US 20070071314 A1), Paragraph [0007].
Regarding claim 23, LEWIS in view of HARVILLE and further in view of BHATTI the method of claim 22, the method further comprising:
LEWIS fails to explicitly teach receiving an empirical feedback, based on one or more of the product recommendation, the user skin color,
However, HARVILLE explicitly teaches receiving an empirical feedback (Fig. 2. Paragraph [0045]-HARVILLE discloses subject 203 can identify additional parameters using, for example, a web interface. These parameters can be used by product recommendation system 220 to further identify the product(s) in which the user is interested. For example, users can indicate that they are interested in clothing, hair coloring, makeup, etc. The users may further indicate specific product groups in which they are interested such as eye makeup, foundation, lipstick, etc. Demographic information may also be collected to further refine a product consultation (wherein the additional parameters are feedback).), based on one or more of the product recommendation (Fig. 1. Paragraph [0024]-HARVILLE discloses in step 140 of FIG. 1, at least one product which corresponds with the classification color is recommended. In embodiments of the present invention, a result is generated in which at least one product is recommended to a user.), the user skin color (Fig. 2. Paragraph [0044]-HARVILLE discloses product recommendation system 220 uses the skin color estimate 413 to map subject 203 to a particular bin or plurality of bins based upon the coloration of the subject.),
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of HARVILLE of receiving an empirical feedback, based on one or more of the product recommendation, the user skin color.
Wherein having LEWIS’s system for determining skin color having receiving an empirical feedback, based on one or more of the product recommendation, the user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and HARVILLE relate to detecting and analyzing skin in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while HARVILLE the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and HARVILLE et al. (US 20070058858 A1), Paragraph [0005].
However, BHATTI explicitly teaches and the transposed user skin color (Fig. 2. Paragraph [0036]-BHATTI discloses image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of BHATTI of and the transposed user skin color.
Wherein having LEWIS’s system for determining skin color having and the transposed user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and BHATTI relate to skin analysis systems, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while BHATTI the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and BHATTI et al. (US 20070071314 A1), Paragraph [0007].
Regarding claim 24, LEWIS in view of HARVILLE explicitly teach the method of claim 13, the method further comprising:
LEWIS in view of HARVILLE fail to explicitly teach calibrating the skin analysis assembly, by taking one or more images of a calibration card using a camera of the processing system, to obtain a calibration transposition that is applied to the user skin image.
However, BHATTI explicitly teaches calibrating the skin analysis assembly (Fig. 2. Paragraph [0036]-BHATTI discloses by comparing the characteristics of control reference color set 208 with the characteristics of the reference color set 204 captured in the image, image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.), by taking one or more images of a calibration card using a camera of the processing system (Fig. 2. Paragraph [0034]-BHATTI discloses system 200 comprises an image capture device 201 for capturing an image 202 comprising a subject (e.g., 203) and a imaged reference color set 204 (wherein the imaged reference color set is a calibration card).), to obtain a calibration transposition that is applied to the user skin image (Fig. 2. Paragraph [0036]-BHATTI discloses image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of BHATTI of calibrating the skin analysis assembly, by taking one or more images of a calibration card using a camera of the processing system, to obtain a calibration transposition that is applied to the user skin image.
Wherein having LEWIS’s system for determining skin color having calibrating the skin analysis assembly, by taking one or more images of a calibration card using a camera of the processing system, to obtain a calibration transposition that is applied to the user skin image.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and BHATTI relate to skin analysis systems, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while BHATTI the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and BHATTI et al. (US 20070071314 A1), Paragraph [0007].
Regarding claim 35, LEWIS in view of HARVILLE and further in view of BHATTI explicitly teach the system of claim 9,
LEWIS fails to explicitly teach wherein the alternative skin color system comprises a set of defined skin colors correlated to products of a product owner, the set of defined skin colors determined by a different system, and.
However, HARVILLE explicitly teaches wherein the alternative skin color system comprises a set of defined skin colors correlated to products of a product owner (Fig. 2. Paragraph [0039]-HARVILLE discloses each of the bins is correlated with a corresponding product. For example, based upon the skin color of the test subjects, a first bin may be associated with a particular shade of foundation (e.g., buff beige) while a second bin may be associated with a second shade of foundation (e.g., creamy natural). In other embodiments of the present invention, each bin may be associated with more than one product. As described above, a product associated with a particular bin may comprise cosmetics, clothing, eyeglasses, jewelry, or another appearance related product.),
the set of defined skin colors determined by a different system (Fig. 2. Paragraph [0038]-HARVILLE discloses the skin colors of a plurality of human test subjects are measured and used by product recommendation system 220 as the range of classification colors 221. In one embodiment, the skin color of each of the test subjects comprises one of classification colors 221.), and
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of HARVILLE of when the average pixel condition color score is below an image condition color threshold, then: removing pixels, from the plurality of user skin image pixels, that exceed the per-pixel condition color threshold; and output a result of the color processing, the result comprising the user skin color.
Wherein having LEWIS’s system for determining skin color having when the average pixel condition color score is below an image condition color threshold, then: removing pixels, from the plurality of user skin image pixels, that exceed the per-pixel condition color threshold; and output a result of the color processing, the result comprising the user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and HARVILLE relate to detecting and analyzing skin in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while HARVILLE the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and HARVILLE et al. (US 20070058858 A1), Paragraph [0005].
LEWIS in view of HARVILLE fail to explicitly teach wherein the transposed user skin color is a determined skin color of the set of determined skin colors.
However, BHATTI explicitly teaches wherein the transposed user skin color is a determined skin color of the set of determined skin colors (Fig. 2. Paragraph [0036]-BHATTI discloses by comparing the characteristics of control reference color set 208 with the characteristics of the reference color set 204 captured in the image, image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a system for user skin color determination of a user, the system comprising: a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of BHATTI of wherein the transposed user skin color is a determined skin color of the set of determined skin colors.
Wherein having LEWIS’s system for determining skin color wherein the transposed user skin color is a determined skin color of the set of determined skin colors.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and BHATTI relate to skin analysis systems, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while BHATTI the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and BHATTI et al. (US 20070071314 A1), Paragraph [0007].
Regarding claim 39, LEWIS in view of HARVILLE and further in view of BHATTI explicitly teach the method of claim 21,
LEWIS fails to explicitly teach wherein the alternative skin color system comprises a set of defined skin colors correlated to products of a product owner, the set of defined skin colors determined by a different system, and.
However, HARVILLE explicitly teaches wherein the alternative skin color system comprises a set of defined skin colors correlated to products of a product owner (Fig. 2. Paragraph [0039]-HARVILLE discloses each of the bins is correlated with a corresponding product. For example, based upon the skin color of the test subjects, a first bin may be associated with a particular shade of foundation (e.g., buff beige) while a second bin may be associated with a second shade of foundation (e.g., creamy natural). In other embodiments of the present invention, each bin may be associated with more than one product. As described above, a product associated with a particular bin may comprise cosmetics, clothing, eyeglasses, jewelry, or another appearance related product.),
the set of defined skin colors determined by a different system (Fig. 2. Paragraph [0038]-HARVILLE discloses the skin colors of a plurality of human test subjects are measured and used by product recommendation system 220 as the range of classification colors 221. In one embodiment, the skin color of each of the test subjects comprises one of classification colors 221.), and
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of HARVILLE of when the average pixel condition color score is below an image condition color threshold, then: removing pixels, from the plurality of user skin image pixels, that exceed the per-pixel condition color threshold; and output a result of the color processing, the result comprising the user skin color.
Wherein having LEWIS’s system for determining skin color having when the average pixel condition color score is below an image condition color threshold, then: removing pixels, from the plurality of user skin image pixels, that exceed the per-pixel condition color threshold; and output a result of the color processing, the result comprising the user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and HARVILLE relate to detecting and analyzing skin in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while HARVILLE the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and HARVILLE et al. (US 20070058858 A1), Paragraph [0005].
LEWIS in view of HARVILLE fail to explicitly teach wherein the transposed user skin color is a determined skin color of the set of determined skin colors.
However, BHATTI explicitly teaches wherein the transposed user skin color is a determined skin color of the set of determined skin colors (Fig. 2. Paragraph [0036]-BHATTI discloses by comparing the characteristics of control reference color set 208 with the characteristics of the reference color set 204 captured in the image, image analysis system 205 can determine a transformation, or "color correction function," which accounts for the discrepancy between the characteristics of imaged reference color set 204 and control reference color set 208.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a system for user skin color determination of a user, the system comprising: a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of BHATTI of wherein the transposed user skin color is a determined skin color of the set of determined skin colors.
Wherein having LEWIS’s system for determining skin color wherein the transposed user skin color is a determined skin color of the set of determined skin colors.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and BHATTI relate to skin analysis systems, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while BHATTI the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and BHATTI et al. (US 20070071314 A1), Paragraph [0007].
Claims 32 and 36 are rejected under 35 U.S.C. 103 as being unpatentable over LEWIS et al. (US 20140341442 A1), hereinafter referenced as LEWIS, in view of HARVILLE et al. (US 20070058858 A1), hereinafter referenced as HARVILLE, and further in view MALLICK et al. (US 20220392032 A1), hereinafter referenced as MALLICK.
Regarding claim 32, LEWIS in view of HARVILLE explicitly teach the system of claim 1, wherein:
LEWIS fails to explicitly teach the average pixel condition color score comprises an average pixel blueness score;
However, HARVILLE explicitly teaches the average pixel condition color score comprises an average pixel blueness score (Fig. 4A. Paragraph [0068]-HARVILLE discloses the luminance (Y) of a pixel may be computed using the following formula: Y=R+G+B where R, G, and B are the red, green, and blue component values of the pixel. Having computed the luminance of each pixel, skin pixel selection component 402 sorts the pixels in order of increasing luminance. Skin pixel selection component 402 then eliminates skin pixels that have a luminance below a lower threshold or above an upper threshold (wherein luminance is the average pixel condition color score and the blue component value is a blueness score).);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of HARVILLE of the average pixel condition color score comprises an average pixel blueness score.
Wherein having LEWIS’s system for determining skin color having the average pixel condition color score comprises an average pixel blueness score.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and HARVILLE relate to detecting and analyzing skin in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while HARVILLE the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and HARVILLE et al. (US 20070058858 A1), Paragraph [0005].
LEWIS in view of HARVILLE fail to explicitly teach the image condition color threshold comprises an image blueness threshold; the per-pixel condition color threshold comprises a per-pixel blueness threshold; and the condition color mask comprises a blueness mask.
However, MALLICK explicitly teaches the image condition color threshold comprises an image blueness threshold (Fig. 9-10. Paragraph [0078]-MALLICK discloses the blue tone value should also be greater than a certain threshold value.);
the per-pixel condition color threshold comprises a per-pixel blueness threshold (Fig. 9-10. Paragraph [0078]-MALLICK discloses the blue tone value should also be greater than a certain threshold value. Therefore, we generate a mean blue hue mask M.sub.1 1008 (FIG. 10) through the conjugation of masks representing the detection of blue-hued pixels 904 as follows: (1) a blue-red comparative threshold mapping M.sub.BR 1002 (FIG. 10); (2) a blue-green comparative threshold mapping M.sub.BG 1004 (FIG. 10); and (3) a blue threshold mapping M.sub.B 1006 (FIG. 10): M.sub.BR=(B−R)>th M.sub.BG=(B−G)>th M.sub.B=B>th M.sub.1=AND(OR(M.sub.BR,M.sub.BG),M.sub.B).); and
the condition color mask comprises a blueness mask (Fig. 10. Paragraph [0077]-MALLICK discloses FIG. 9A provides a diagrammatic flowchart of a first heuristic method 900 calculating a detection mask M.sub.31012 (FIG. 10) from the conjugation of a mean blue hue mask M.sub.1 1008 (FIG. 10) and a threshold blue hue mask M.sub.2 1010 (FIG. 10).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of MALLICK of the image condition color threshold comprises an image blueness threshold; the per-pixel condition color threshold comprises a per-pixel blueness threshold; and the condition color mask comprises a blueness mask.
Wherein having LEWIS’s system for determining skin color having the image condition color threshold comprises an image blueness threshold; the per-pixel condition color threshold comprises a per-pixel blueness threshold; and the condition color mask comprises a blueness mask.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and MALLICK relate to detecting and analyzing colors in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while MALLICK there is a need to provide techniques and algorithms for improved tone mapping and for improved generation of HDR tuned images without this significant computational burden. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and MALLICK et al. (US 20220392032 A1), Paragraph [0005].
Regarding claim 36, LEWIS in view of HARVILLE explicitly teach the method of claim 13, wherein:
LEWIS fails to explicitly teach the average pixel condition color score comprises an average pixel blueness score;
However, HARVILLE explicitly teaches the average pixel condition color score comprises an average pixel blueness score (Fig. 4A. Paragraph [0068]-HARVILLE discloses the luminance (Y) of a pixel may be computed using the following formula: Y=R+G+B where R, G, and B are the red, green, and blue component values of the pixel. Having computed the luminance of each pixel, skin pixel selection component 402 sorts the pixels in order of increasing luminance. Skin pixel selection component 402 then eliminates skin pixels that have a luminance below a lower threshold or above an upper threshold (wherein luminance is the average pixel condition color score and the blue component value is a blueness score).);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of HARVILLE of the average pixel condition color score comprises an average pixel blueness score.
Wherein having LEWIS’s system for determining skin color having the average pixel condition color score comprises an average pixel blueness score.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and HARVILLE relate to detecting and analyzing skin in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while HARVILLE the customer is presented with a smaller range of products from which to choose, but which are more suited for that customer based upon her needs. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and HARVILLE et al. (US 20070058858 A1), Paragraph [0005].
LEWIS in view of HARVILLE fail to explicitly teach the image condition color threshold comprises an image blueness threshold; the per-pixel condition color threshold comprises a per-pixel blueness threshold; and the condition color mask comprises a blueness mask.
However, MALLICK explicitly teaches the image condition color threshold comprises an image blueness threshold (Fig. 9-10. Paragraph [0078]-MALLICK discloses the blue tone value should also be greater than a certain threshold value.);
the per-pixel condition color threshold comprises a per-pixel blueness threshold (Fig. 9-10. Paragraph [0078]-MALLICK discloses the blue tone value should also be greater than a certain threshold value. Therefore, we generate a mean blue hue mask M.sub.1 1008 (FIG. 10) through the conjugation of masks representing the detection of blue-hued pixels 904 as follows: (1) a blue-red comparative threshold mapping M.sub.BR 1002 (FIG. 10); (2) a blue-green comparative threshold mapping M.sub.BG 1004 (FIG. 10); and (3) a blue threshold mapping M.sub.B 1006 (FIG. 10): M.sub.BR=(B−R)>th M.sub.BG=(B−G)>th M.sub.B=B>th M.sub.1=AND(OR(M.sub.BR,M.sub.BG),M.sub.B).); and
the condition color mask comprises a blueness mask (Fig. 10. Paragraph [0077]-MALLICK discloses FIG. 9A provides a diagrammatic flowchart of a first heuristic method 900 calculating a detection mask M.sub.31012 (FIG. 10) from the conjugation of a mean blue hue mask M.sub.1 1008 (FIG. 10) and a threshold blue hue mask M.sub.2 1010 (FIG. 10).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of MALLICK of the image condition color threshold comprises an image blueness threshold; the per-pixel condition color threshold comprises a per-pixel blueness threshold; and the condition color mask comprises a blueness mask.
Wherein having LEWIS’s system for determining skin color having the image condition color threshold comprises an image blueness threshold; the per-pixel condition color threshold comprises a per-pixel blueness threshold; and the condition color mask comprises a blueness mask.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and MALLICK relate to detecting and analyzing colors in images, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin. while MALLICK there is a need to provide techniques and algorithms for improved tone mapping and for improved generation of HDR tuned images without this significant computational burden. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and MALLICK et al. (US 20220392032 A1), Paragraph [0005].
Claims 33 and 37 are rejected under 35 U.S.C. 103 as being unpatentable over LEWIS et al. (US 20140341442 A1), hereinafter referenced as LEWIS, in view of HARVILLE et al. (US 20070058858 A1), hereinafter referenced as HARVILLE, and further in view MALLICK et al. (US 20220392032 A1), hereinafter referenced as MALLICK, and further in view of MACKINNON et al. (WO 2019144247 A1), MACKINNON.
Regarding claim 33, LEWIS in view of HARVILLE and further in view of MALLICK explicitly teach the system of claim 32,
Although MALLICK explicitly teaches wherein the image blueness threshold, LEWIS in view of HARVILLE and further in view of MALLICK fail to explicitly teach wherein the image redness threshold is based on one or more of a processing power of the system, a desired speed and a desired accuracy of the user skin color.
However, MACKINNON explicitly teaches wherein the image blueness threshold (Fig. 7. Paragraph [0011]-MACKINNON discloses digital color images can be based on color or gray scale thresholding, using RGB image data, or using other color spaces such as YCR or CIE 1976 L*a*b* color space and some kind of feature recognition and classification algorithm. Further in paragraph [0050-0051]-MACKINNON discloses The difference between the a* image before and after smoothing is used to find the redness change in each pixel [620] Pixels with large differences in redness are then considered as an acne (Otsu thresholding) and used to create a binary image of acne lesions [630] FIG. 7 shows an exemplary RGB image exhibiting a user-captured image [700], a* image before [710] and after Gaussian filter implementation [720], difference of redness [730], and generated binary image of acne lesions [740]) is based on one or more of a processing power of the system, a desired speed, and a desired accuracy of the user skin color (Fig. 7. Paragraph [0041]-MACKINNON discloses the processing software may be installed on the mobile device. At this time, the processing capability of mobile devices is insufficient to provide sufficient processing capability for some applications. For those applications where the processing capability of the mobile device is sufficient, data processing may occur on the mobile device. In some embodiments, the system and method comprises capturing images of the face using the mobile application on the smart phone and uploading the images to a cloud server for storage and processing.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE and further in view of MALLICK of a system for user skin color determination of a user, the system comprising: a processing system comprising one or more processors, configured to: obtain a user skin image of the user, comprising a plurality of user skin image pixels; perform color processing on the user skin image to arrive at a user skin color, comprising: with the teachings of MACKINNON of wherein the image blueness threshold is based on one or more of a processing power of the system, a desired speed and a desired accuracy of the user skin color.
Wherein having LEWIS’s system for determining skin color wherein the image blueness threshold is based on one or more of a processing power of the system, a desired speed and a desired accuracy of the user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and MACKINNON relate to analyzing skin images of a person, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while MACKINNON it is a goal of this invention to overcome existing difficulties in observing the evolution of acne over time without the need for face and head positioning fixtures and complex imaging devices that require deployment in a clinical or laboratory setting and to provide individuals who may be suffering from chronic acne with digital tools to assess and monitor the progress of their disease using their smart phone or tablet as a mobile medical device. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and MACKINNON et al. (WO 2019144247 A1), Paragraph [0013].
Regarding claim 37, LEWIS in view of HARVILLE and further in view of MALLICK fail to explicitly teach the method of claim 36,
Although MALLICK explicitly teaches wherein the image blueness threshold, LEWIS in view of HARVILLE and further in view of MALLICK fail to explicitly teach wherein the image blueness threshold is based on one or more of a processing power of the system, a desired speed and a desired accuracy of the user skin color.
However, MACKINNON explicitly teaches wherein the image blueness threshold (Fig. 7. Paragraph [0011]-MACKINNON discloses digital color images can be based on color or gray scale thresholding, using RGB image data, or using other color spaces such as YCR or CIE 1976 L*a*b* color space and some kind of feature recognition and classification algorithm. Further in paragraph [0050-0051]-MACKINNON discloses The difference between the a* image before and after smoothing is used to find the redness change in each pixel [620] Pixels with large differences in redness are then considered as an acne (Otsu thresholding) and used to create a binary image of acne lesions [630] FIG. 7 shows an exemplary RGB image exhibiting a user-captured image [700], a* image before [710] and after Gaussian filter implementation [720], difference of redness [730], and generated binary image of acne lesions [740]) is based on one or more of a processing power of the system, a desired speed, and a desired accuracy of the user skin color (Fig. 7. Paragraph [0041]-MACKINNON discloses the processing software may be installed on the mobile device. At this time, the processing capability of mobile devices is insufficient to provide sufficient processing capability for some applications. For those applications where the processing capability of the mobile device is sufficient, data processing may occur on the mobile device. In some embodiments, the system and method comprises capturing images of the face using the mobile application on the smart phone and uploading the images to a cloud server for storage and processing.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of LEWIS in view of HARVILLE and further in view of MALLICK of a method for user skin color determination of a user, the method comprising: obtaining, by a processing system, a user skin image of the user, comprising a plurality of user skin image pixels; performing, by one or more processors of the processing system, color processing on the user skin image to arrive at a user skin color, comprising: determining an average pixel condition color score for the plurality of user skin image pixels in the user skin image with the teachings of MACKINNON of wherein the image blueness threshold is based on one or more of a processing power of the system, a desired speed and a desired accuracy of the user skin color.
Wherein having LEWIS’s system for determining skin color wherein the image blueness threshold is based on one or more of a processing power of the system, a desired speed and a desired accuracy of the user skin color.
The motivation behind the modification would have been to obtain a system for determining skin color that enhances the accuracy of detecting skin in an image and determining skin color in an image. Since both LEWIS and MACKINNON relate to analyzing skin images of a person, wherein LEWIS allows more accurate generation of a face image mask and robust selection of faces and skin, while MACKINNON it is a goal of this invention to overcome existing difficulties in observing the evolution of acne over time without the need for face and head positioning fixtures and complex imaging devices that require deployment in a clinical or laboratory setting and to provide individuals who may be suffering from chronic acne with digital tools to assess and monitor the progress of their disease using their smart phone or tablet as a mobile medical device. Please see LEWIS et al. (US 20140341442 A1), Paragraph [0020], and MACKINNON et al. (WO 2019144247 A1), Paragraph [0013].
Allowable Subject Matter
Claims 8, 20, 34, and 38, along with dependent claims are therefrom objected to as being dependent upon rejected base claims, claims 1, 5, 13, 17, 19, 32, and 36 but would be allowable if rewritten in independent form including all of the limitations of the base claims and any intervening claims once the claim objection and 112(a) new matter rejections are overcome.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 8, the prior arts fail to explicitly teach wherein the calculating the per-pixel redness threshold comprises testing various per-pixel redness threshold values and choosing the per-pixel redness threshold value that minimizes the delta E from skin images that already had CIELAB color space values, as claimed in claim in 8.
Regarding claim 20, the prior arts fail to explicitly teach wherein the calculating the per-pixel redness threshold comprises testing various per-pixel redness threshold values and choosing the per-pixel redness threshold value that minimizes the delta E from skin images that already had CIELAB color space values, as claimed in claim in 20.
Regarding claim 34, the prior arts fail to explicitly teach wherein the calculating the per-pixel blue threshold comprises testing various per-pixel blueness threshold values and choosing the per-pixel blueness threshold value that minimizes the delta E from skin images that already had CIELAB color space values as claimed in claim in 34.
Regarding claim 38, the prior arts fail to explicitly teach wherein the calculating the per-pixel blue threshold comprises testing various per-pixel blueness threshold values and choosing the per-pixel blueness threshold value that minimizes the delta E from skin images that already had CIELAB color space values, as claimed in claim in 38.
Conclusion
Listed below are the prior arts made of record and not relied upon but are considered pertinent to applicant’s disclosure.
ROBINSON et al. (US 20220005227 A1) - Digital imaging systems and methods are described for determining a user-specific skin redness value of a user's skin after removing hair. An example method may be performed by one or more processors and may include aggregating training images comprising pixel data of skin of individuals after removing hair. A skin redness model may be trained using the training images to output skin redness values associated with a degree of skin redness from least to most red. The method may include receiving an image of a user including pixel data of the user's skin after hair is removed from the skin, analyzing the image using the skin redness model to determine a user-specific skin redness value, generating a user-specific recommendation designed to address a feature identifiable within the pixel data of the user's skin, and rendering the recommendation on a display screen of a user computing device…Abstract, Fig. 1.
PAYONK et al. (US 20080080766 A1) - An imaging system and method has digital image capture and analysis capability. The digital images may be taken in a variety of illumination conditions, with the skin response indicating skin condition. The digital images may be converted from RGB format to L*a*b* format and analyzed quantitatively to assess color and brightness. The color/brightness information from the digital images may be used to assess skin condition and changes thereof, as well as selecting cosmetics provided in a range of colors. The color information gleaned from the digital images of a population may be utilized to identify a palette of colors for cosmetics or to aid in conducting clinical studies…Abstract, Fig. 5.
KORICHI et al. (US 20120300050 A1) - A method and apparatus for characterizing the tone of the skin or integuments uses an apparatus capturing a digital image of a skin zone. The image is defined by a multiplicity of pixels (N) and transmitted to a digital image processing device for splitting the digital image into R, G and B colour planes. The apparatus includes means for extracting each of these planes R, G, B; and on each plane, calculation means for logging the grey level value for each of the pixels, i.e. N values, which are optionally processed to obtain a value characteristic of the grey levels for each plane, corresponding to a value characteristic of the colour; as well as the luminosity value L*. The apparatus also characterizes the tone of the skin or integuments on the basis of the combination of the value characteristic of the colour and of the Luminosity value L*…Abstract, Fig. 3.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/ETHAN N WOLFSON/Examiner, Art Unit 2673
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673
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