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 .
Drawings
The drawings were received on 09/09/2024. These drawings are accepted.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
Image correction unit in claims 1-13
Authentication processing unit in claims 1 and 13
Display unit in claims 11-12
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1 and 13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Iwata et al. (US20150020181, hereinafter “Iwata”)
[Claim 1] Iwata teaches A biometric authentication system ([0002] “biometric authentication,”) comprising: a storage device that stores biometric features, ([0020] “extracting the palm print shape and the vein shape in the palm respectively for template from said one reflection image to perform processing to generate the template data, and. wherein template data storage unit is configured for storing said template data.” and [0058] “The template data storage unit 24 may be made up of e.g., a computer memory.”)
an imaging device for capturing biometrics, ([0047] “The authentication image acquisition unit 12 may be made up of an appropriate device such as digital camera and image scanner.”)
an image correction unit that converts the image quality of the image captured by the imaging device, ([0110] “R signal, G signal and B signal in RGB color space are transformed into R' signal, G' signal and B' signal in RGB color system by multiplying the chroma (value of S) in the range of H=0 to 60 degrees on HSV space by 0.1, and shifting the hue (H)+115 degrees as a whole.” Is understood to be the same as the claimed converts the image quality in light of instant specifications [0084]) and
an authentication processing unit that performs biometric authentication using the image output by the image correction unit, ([0081] “color space transformable for RGB color space (e.g., YCbCr, YIQ, Luv, Lab, XYZ) may be used instead of RGB color space to extract the features of the data in the template image or in the authentication image.”)
wherein the image correction unit generates an image before color correction of one or more images in which biometrics is captured, ([0047] “The authentication image acquisition unit 12 is configured to acquire at least one reflection image (i.e. image data) to form by the light which is emitted from the authentication light source 11, and is reflected on the palm of the human body.” Is understood to be the same as the claimed generates an image before color correction because it is the initial captured image before color correction is implemented)
transforms the pre-color correction image ([0110] “R signal, G signal and B signal in RGB color space are transformed into R' signal, G' signal and B' signal in RGB color system”) by a plurality of values within a predetermined search range for color information ([0110] “…by multiplying the chroma (value of S) in the range of H=0 to 60 degrees on HSV space by 0.1,”) to generate a plurality of color information transformed images, ([0110] “… and shifting the hue (H)+115 degrees as a whole.” Is understood to be the same as the claimed color information transformed images in light of instant specifications [0084])
selects a color information conversion image that best represents the biometric feature ([0079] “the second template data can be generated as a gray scale image in which the vein pattern is emphasized.” And [0027] “reflection image for template as the template data,”) for each biometric feature from the plurality of color information conversion images,
([0072] “find out the data information in which the shape of veins appears intensively, and remove the data information in which vein information does not appear easily.”) and
searches the optimal color information ([0078] “the optimal coefficient value as an experimental value is GPvein=(0.6*R'+0.6*M'-0.2*G').” and [0079] “The calculation of said GPvein is performed for each pixel.”) for each biometric feature ([0079] “If the calculation for each pixel results in 255 or more, the value of GPvein is set to 255. In this way, the second template data can be generated as a gray scale image in which the vein pattern is emphasized.”) based on the color information ([0076] “R signal and G signal in RGB color space are transformed into R' signal and G' signal which are generated by attenuating chroma (value of 5) by 30% in negative direction on HSV space.”) to obtain the selected color information conversion image. ([0077] “G Pvein: Gray-scale data obtained from R' signal, G' signal and M' signal values”)
[Claim 13] The method herein has been executed and performed by the system of claim 1 and is likewise rejected.
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 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 2-10 are rejected under 35 U.S.C. 103 as being unpatentable over Iwata et al. (US20150020181, hereinafter “Iwata”) and in view of Pranskevichus et al (US20230267583, hereinafter “Pranskevichus”)
[Claim 2] Iwata teaches The biometric authentication system according to claim 1, wherein
Iwata does not explicitly teach the image correction unit generates the pre-color- corrected image by Generative Adversarial Network from a plurality of images captured by the imaging device.
Pranskevichus teaches the image correction unit generates the pre-color- corrected image ([0006] “a neural net removes artifacts and upscales images end-to-end, and auxiliary networks like HDR improve colors, white balance, etc.” is understood to be the same as the claimed generates the pre-color corrected image in light of instant specifications [0054] ) by Generative Adversarial Network from a plurality of images captured by the imaging device. ([0006] “Generative adversarial networks can be used to generate new details and restore features of an image.”)
It would have been obvious to persons of ordinary skill in the art before the effective filing date of the claimed invention to modify Iwata to have generate an image that is white balanced as taught by Pranskevichus to arrive at the claimed invention discussed above. The motivation for the proposed modification would have been because (Pranskevichus et al [0005] “improvement to image enhancement techniques (reduced cost, higher speed, higher quality end results, etc.) would be considered advantageous.”)
[Claim 3] Iwata and Pranskevichus teach The biometric authentication system according to claim 2,
Iwata teaches wherein the image correction unit searches the optimal color information ([0078] “the optimal coefficient value as an experimental value is GPvein=(0.6*R'+0.6*M'-0.2*G').” and [0079] “The calculation of said GPvein is performed for each pixel.”) for each biometric feature ([0079] “If the calculation for each pixel results in 255 or more, the value of GPvein is set to 255. In this way, the second template data can be generated as a gray scale image in which the vein pattern is emphasized.”) by narrowing the search range based on the color information ([0076] “R signal and G signal in RGB color space are transformed into R' signal and G' signal which are generated by attenuating chroma (value of 5) by 30% in negative direction on HSV space.”)to obtain the selected color information conversion image. ([0077] “G Pvein: Gray-scale data obtained from R' signal, G' signal and M' signal values”)
[Claim 4] Iwata and Pranskevichus teach The biometric authentication system according to claim 3,
Iwata teaches wherein the image correction unit calculates matching score ([0103] “using the degree of similarity.”) of the biometric feature ([0104] “the feature of the vein pattern and the feature of the shape of the palm print in the palm of the person to be authenticated are extracted from a single original image data photographed”) by matching the same finger and another finger in the color information conversion image, ([0107] “the matching unit performs the first authentication by comparing the first authentication data with the first template data.”) and searches the color information of the color information conversion image in which the matching score of the same finger and the matching score of another finger are most separated for as the optimal value. ([0114] “If the calculation for each pixel results in zero or less, the value of GPvein is set to 0, and if the calculation result for each pixel becomes 255 or more, the value of GPvein is set to 255. Thus, the second template data can be generated as a gray scale image where the vein pattern is emphasized.”)
[Claim 5] Iwata and Pranskevichus teach The biometric authentication system according to claim 3, wherein the image correction unit searches the color information that maximizes the evaluated value of the contrast of the
biometric information ([0114] “GPvein is performed for each pixel. … the second template data can be generated as a gray scale image where the vein pattern is emphasized.” Is understood to be the same as the claimed maximizes the evaluated value of the contrast in light of instant specifications [0089] ) in the color information conversion image as the optimal value. ([0078] “the optimal coefficient value as an experimental value is GPvein”)
[Claim 6] Iwata and Pranskevichus teach The biometric authentication system according to claim 3,
Iwata does not explicitly teach wherein the image correction unit converts the color information by converting the color temperature.
Pranskevichus teaches wherein the image correction unit converts the color information by converting the color temperature. ([0006] “a neural net removes artifacts and upscales images end-to-end, and auxiliary networks like HDR improve colors, white balance, etc.” is understood to be the same as the claimed by converting the color temperature in light of instant specifications [0046])
It would have been obvious to persons of ordinary skill in the art before the effective filing date of the claimed invention to modify Iwata to have converts the color information by converting the color temperature as taught by Pranskevichus to arrive at the claimed invention discussed above. The motivation for the proposed modification would have been because (Pranskevichus et al [0005] “improvement to image enhancement techniques (reduced cost, higher speed, higher quality end results, etc.) would be considered advantageous.”)
[Claim 7] Iwata and Pranskevichus teach The biometric authentication system according to claim 3,
Iwata teaches wherein the image correction unit converts the color information by converting the hue. ([0077] “GPvein: Gray-scale data obtained from R' signal, G' signal and M' signal values”)
[Claim 8] Iwata and Pranskevichus teach The biometric authentication system according to claim 3,
Iwata teaches wherein the image correction unit corrects luminance gradient caused by non-biometric features in the image. (“therefore the light source environment would vary remarkably at the times for acquisition of the two images. According to the processing in the second modification, template data or the authentication data which are robust in the light source environment can be obtained. ”is understood to be the same as the claimed corrects luminance gradient in light of instant specifications [0099])
[Claim 9] Iwata and Pranskevichus teach The biometric authentication system according to claim 3,
Iwata teaches wherein the image correction unit estimates the average intensity ([0088] “binarization of the template data (TD) can be performed with a popular technique, such as moving average in each pixel or each block,”)of multiple wavelength bands in the image before color correction. ([0110] “R signal, G signal and B signal in RGB color space are transformed into R' signal, G' signal and B' signal in RGB color system” this is after the average performed in Iwata [0088])
[Claim 10] Iwata and Pranskevichus teach The biometric authentication system according to claim 3, wherein
Iwata teaches The image correction unit changes the hue for the image of the average intensity of multiple wavelength bands in the image ([0110] “R signal, G signal and B signal in RGB color space are transformed into R' signal, G' signal and B' signal in RGB color system” this is after the average performed in Iwata [0088]) before color correction, ([0111] “In consequence of the above-described processing, the data of R' signal, G' signal, B' signal and M' signal spaces, which are different from the data of the original RGB space and CMYK space, can be obtained.”)
calculates the degree of difference ([0064] “Next, individual authentication is performed by comparing template data with for authentication data using the degree of similarity between them.” ) The degree of difference is defined in the specifications to be calculated using “Normalized Cross Correlation (NCC) and Zero Mean Normalized Cross Correlation (ZNCC)” in light of instant specifications [0134]. As per https://en.wikipedia.org/wiki/Cross-correlation “cross correlation” is a measure of similarity and not a measure of difference which is why the examiner cites from Iwata the relevant citation for degree of similarity) between the image in the first wavelength band and the image in the second wavelength band, and the degree of difference between the image in the first wavelength band and the image in the third wavelength band, ([0110] “[0110] R signal, G signal and B signal in RGB color space are transformed into R' signal, G' signal and B' signal in RGB color system by multiplying the chroma (value of S) in the range of H=0 to 60 degrees on HSV space by 0.1, and shifting the hue (H)+115 degrees as a whole.”) calculates the sum of the two acquired degrees of difference, ([0113] “GPvein=(0.5*R'+0.1*G'-0.05*B'-0.1*M')” is understood to be the same as the claimed sum of the two degrees of difference, in Iwata it is the sum of 0.5*R’ + 0.1*G’ ) and
selects the hue that maximizes the sum of the degree of differences as the optimal value. ([0113] “For example, the coefficient value optimal as an experimental value is; GPvein=(0.5*R'+0.1*G'-0.05*B'-0.1*M')”)
Allowable Subject Matter
Claims 11-12 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Iwata et al US20150020181 discloses utilizing ambient light as a light source but does not render obvious the claimed combination as a whole
Pranskevichus et al US20230267583 discloses utilizing a generative adversarial network to improve white balance but does not render obvious the claimed combination as a whole
Wong et al US20120293472 discloses determining the direction of ambient light incident on an ambient light sensor but does not render obvious the claimed combination as a whole
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure:
Khoury et al et al US20180226079 teaches biometric authentication and color correction on the images
Miura et al WO2017082100 teaches biometric authentication device where the image of the palm is taken and the orientation of the image is corrected.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to OWAIS MEMON whose telephone number is (571)272-2168. The examiner can normally be reached M-F (7:00am - 4:00pm) CST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Gregory Morse can be reached at (571) 272-3838. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/OWAIS I MEMON/Examiner, Art Unit 2663
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