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
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. KR10-2022-0169447, filed on 7th December, 2022.
Acknowledgment is made of applicant's claim for foreign priority based on an application filed in South Korea on 4th November, 2022. It is noted, however, that applicant has not filed a certified copy of the KR10-2022-0145718 application as required by 37 CFR 1.55.
Specification
The abstract of the disclosure is objected to because the word count is at 171 words, which exceeds the 150-word count limit. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Claim Rejections - 35 USC § 103
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, 4, 9, 11, 14, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US 8379972 B1), hereinafter referenced as Wang, in view of Ido (US 20190079707 A1).
Regarding Claim 1, Wang discloses an electronic device (Wang, [Col. 16, Line(s) 15]: teaches computer system 1000 <read on electronic device>) comprising:
memory storing one or more computer programs (Wang, [Col. 16, Line(s) 1-12]: teaches computer system 1000 including system memory 1020 that is configured to store program instructions and/or data <read on computer programs>); and
one or more processors communicatively coupled to the memory (Wang, [Col. 16, Line(s) 1-12]: teaches computer system 1000 including system memory 1020 that is configured to store program instructions and/or data that is accessible by processor 1010), wherein
the one or more computer programs include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to (Wang, [Col. 16, Line(s) 1-2]: teaches system memory 1020 being configured to store program instructions and/or data accessible by processor 1010):
receive a user input related to image quality of a first image (Wang, [Col. 14, Line(s) 44-66]: teaches receiving user input 904 through user interface 940 for modifying input image 900 <read on first image>, where a color decontamination module 910 accesses input image 900; [Col. 13, Line(s) 37-43]: teaches a slider that modifies the decontamination amount <read on image quality> of the input image as shown in FIG. 8A),
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[[determine whether a transparent region exists in the first image,]]
[[determine a plurality of transparent pixels corresponding to the transparent region when the transparent region exists in the first image,]]
extract contour pixels adjacent to a pixel corresponding to an object included in the first image among the plurality of transparent pixels (Wang, [Col. 5, Line(s) 53-57]: teaches a border region <read on contour pixels> between a foreground region and background region of an input image; [Col. 7, Line(s) 31-33]: teaches the distance computed for each pixel in the border region is the distance to the nearest pixel <read on adjacent pixel> of the foreground),
change color information about each pixel included in a first set of contour pixels among the extracted contour pixels based on color information about pixels adjacent to each pixel (Wang, [Col. 11, Line(s) 54-61]: teaches applying pixel-wise luminance blending on decontaminated pixels <read on changed color information> in the border region <read on first set of contour pixels> of the image),
generate a second image including the contour pixels of the changed color information (Wang, [Col. 12, Line(s) 47-54]: teaches generating a final version of the color decontaminated image <read on second image>, which includes "the estimated foreground colors of pixels in the border region after color decontamination has been applied"), and
apply an image quality enhancement algorithm to the second image (Wang, [Col. 12, Line(s) 47-54]: teaches up-sampling <read on applied image quality enhancement> the final version of the color decontaminated image).
However, Wang does not expressly disclose
determine whether a transparent region exists in the first image, and
determine a plurality of transparent pixels corresponding to the transparent region when the transparent region exists in the first image.
Ido discloses
determine whether a transparent region exists in the first image (Ido, [0052]: teaches determining if a processing target region 1201 <read on transparent region> includes fully transparent pixels and not-fully transparent pixels), and
determine a plurality of transparent pixels corresponding to the transparent region when the transparent region exists in the first image (Ido, [0052]: teaches determining the fully transparent and not-fully transparent pixels in the processing target region 1201).
Ido is analogous art with respect to Wang because they are from the same field of endeavor, namely modifying input images for alpha transparency effects. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to have the system determine which processing target regions include fully transparent and not-fully transparent pixels as taught by Ido into the teaching of Wang. The suggestion for doing so would allow for converted images to have improved and smoother edges surrounding the subject, thereby resulting in a higher quality cutout region. Therefore, it would have been obvious to combine Ido with Wang.
Regarding Claim 11, it recites the limitations that are similar in scope to Claim 1, but in a method. As shown in the rejection, the combination of Wang and Ido discloses the limitations of Claim 1. Additionally, Wang discloses a method performed by an electronic device, the method (Wang, [Col. 15, Line(s) 14-17]: teaches a color decontamination method that is executed on one or more computer systems <read on electronic device>) comprising:…
Thus, Claim 11 is met by Wang according to the mapping presented in the rejection of Claim 1, given the electronic device corresponds to a method.
Regarding Claim 19, it recites the limitations that are similar in scope to Claim 1, but in one or more non-transitory computer-readable storage media. As shown in the rejection, the combination of Wang and Ido discloses the limitations of Claim 1. Additionally, Wang discloses one or more non-transitory computer-readable storage media storing one or more computer programs including computer-executable instructions that, when executed by one or more processors of an electronic device individually or collectively, cause the electronic device to perform operations (Wang, [Col. 16, Line(s) 1-7]: teaches system memory 1020 of system 1000 <read on electronic device> that is configured to store <read on operations> executable program instructions and/or data accessible <read on computer programs> by processor 1010, where system memory 1020 is implemented as a non-volatile/flash-type memory <read on non-transitory computer-readable storage media>), the operations comprising:…
Thus, Claim 19 is met by Wang according to the mapping presented in the rejection of Claim 1, given the electronic device corresponds to one or more non-transitory computer-readable storage media.
Regarding Claims 4 and 14, the combination of Wang and Ido discloses the electronic device and the method of Claims 1 and 11 respectively. Additionally, Wang further discloses wherein the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to:
obtain a third image of enhanced image quality from the second image (Wang, [Col. 10, Line(s) 28-35]: teaches repeating the process of determining and estimating pixel values in the border region, which is interpreted as taking a generated output image <read on second image> as input; [Col. 12, Line(s) 47-54]: teaches generating a final version of the color decontaminated image <read on third image>, which includes "the estimated foreground colors of pixels in the border region after color decontamination has been applied," where the output image is then up-scaled <read on image quality enhancement>), and
[[set color information about pixels corresponding to the transparent region of the first image in the third image to "0" to]] generate a fourth image (Wang, [Col. 12, Line(s) 47-54]: teaches generating a final version of the color decontaminated image <read on fourth image>, which includes "the estimated foreground colors of pixels in the border region after color decontamination has been applied").
However, Wang does not expressly disclose
set color information about pixels corresponding to the transparent region of the first image in the third image to "0" to generate a fourth image.
Ido discloses
set color information about pixels corresponding to the transparent region of the first image in the third image to "0" to generate a fourth image (Ido, FIG. 8B teaches color information (R, G, B, A) of an input image <read on first image> being set to zero).
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Ido is analogous art with respect to Wang because they are from the same field of endeavor, namely modifying input images for alpha transparency effects. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to have the system determine which processing target regions include fully transparent and not-fully transparent pixels as taught by Ido into the teaching of Wang. The suggestion for doing so would allow for converted images to have improved and smoother edges surrounding the subject, thereby resulting in a higher quality cutout region. Therefore, it would have been obvious to combine Ido with Wang.
Regarding Claim 9, the combination of Wang and Ido discloses the electronic device of Claim 1. Wang does not expressly disclose the limitations of Claim 9; however, Ido discloses wherein the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to:
set color information about all pixels corresponding to the transparent region using a color information setting method for the contour pixels,set color information about pixels corresponding to a remaining transparent region of the first image to an average value of color information about pixels included in a recent set of contour pixels generated most recently, orset color information about all pixels corresponding to the transparent region to a value representing gray (Ido, [0045]: teaches processing target regions that include transparent and semi-transparent pixels <read on all pixels of transparent region> being gray (i.e.,
(
R
,
G
,
B
,
A
)
=
(
50
,
50
,
50
,
50
)
) <read on color information>).
Ido is analogous art with respect to Wang because they are from the same field of endeavor, namely modifying input images for alpha transparency effects. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to have the system determine which processing target regions include fully transparent and not-fully transparent pixels as taught by Ido into the teaching of Wang. The suggestion for doing so would allow for converted images to have improved and smoother edges surrounding the subject, thereby resulting in a higher quality cutout region. Therefore, it would have been obvious to combine Ido with Wang.
Claims 2-3, 8, 10, 12-13, 18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US 8379972 B1), hereinafter referenced as Wang, in view of Ido (US 20190079707 A1) as applied to Claims 1, 11, and 19 above respectively, and further in view of Navasardyan et al. (US 20220383459 A1), hereinafter referenced as Navasardyan.
Regarding Claims 2 and 12, the combination of Wang and Ido discloses the electronic device and the method of Claims 1 and 11 respectively. The combination of Wang and Ido does not expressly disclose the limitations of Claims 2 and 12; however, Navasardyan discloses wherein the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to:
perform a function a) of identifying locations of pixels of the transparent region adjacent to pixels included in the first set and having the changed color information (Navasardyan, [0030]: teaches iteratively identifying missing boundaries <read on locating pixels in transparent region> in image data after replacement pixel data units are generated for the current missing boundary),
perform a function b) of extracting the pixels whose locations are identified to generate a second set of contour pixels (Navasardyan, [0046]: teaches determining a missing boundary and a missing boundary patch in a missing region <read on location> collection for a given iteration, where "in each iteration, a missing region boundary
∂
M
t
, of the missing region
M
t
, is determined <read on extracting pixels> and is filled"; [0030]: teaches "a new set of replacement pixel data units <read on second set of contour pixels> are generated for the missing boundary pixel data units"), and
perform a function c) of setting color information about each pixel included in the second set based on the color information about pixels adjacent to each pixel (Navasardyan, [0030]: teaches iteratively identifying missing boundaries in image data after replacement pixel data units <read on second set> are generated for the current missing boundary, where "a new set of replacement pixel data units are generated for the new missing boundary pixel data units"; [0046]: teaches determining a missing boundary and a missing boundary patch <read on color information> in a missing region).
Navasardyan is analogous art with respect to Wang, in view of Ido because they are from the same field of endeavor, namely processing and analyzing input images for transparent/missing regions. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to have the system perform iterative identification of missing boundaries and associated missing boundary patches (i.e., textures) in a given image as taught by Navasardyan into the teaching of Wang, in view of Ido. The suggestion for doing so would allow the system to generate new replacement pixel sets in a specific order, thereby allowing for an in-painting process that is coherent and not random. Therefore, it would have been obvious to combine Navasardyan with Wang, in view of Ido.
Regarding Claims 3 and 13, the combination of Wang, Ido, and Navasardyan discloses the electronic device and the method of Claims 2 and 12 respectively. The combination of Wang and Ido does not expressly disclose the limitations of Claims 3 and 13; however, Navasardyan discloses wherein the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to:
generate a specified number of sets of the contour pixels by repeating the function a), the function b), and the function c) to set color information about pixels included in each set (Navasardyan, [0032]: teaches performing an iterative <read on repeating> search for missing boundaries until all missing boundaries are exhausted from the missing region of the image data, where "the number of iterations is limited to a particular number <read on specified number of sets of contour pixels>"), and
omit an operation of identifying locations of pixels of the transparent region adjacent to a pixel included in a most recently generated set when setting color information about the pixel included in the most recently generated set (Navasardyan, [0032]: teaches performing an iterative search for missing boundaries <read on identified locations of pixels of transparent regions> until all missing boundaries are exhausted from the missing region <read on transparent region> of the image data as shown in FIG. 3, where the iterative search processes neighboring pixels; [0030]: teaches a new set of replacement pixel data units are generated <read on most recently generated set> for the new missing boundary pixel data units <read on adjacent pixels>, which is interpreted to be setting color information for each pixel data unit in the new set of replacement pixel data units).
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Navasardyan is analogous art with respect to Wang, in view of Ido because they are from the same field of endeavor, namely processing and analyzing input images for transparent/missing regions. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to have the system perform iterative identification of missing boundaries and associated missing boundary patches (i.e., textures) in a given image as taught by Navasardyan into the teaching of Wang, in view of Ido. The suggestion for doing so would allow the system to generate new replacement pixel sets in a specific order, thereby allowing for an in-painting process that is coherent and not random. Therefore, it would have been obvious to combine Navasardyan with Wang, in view of Ido.
Regarding Claims 8 and 18, the combination of Wang and Ido discloses the electronic device and the method of Claims 1 and 11 respectively. Additionally, Wang further discloses wherein the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to:
[[identify a number of sets of the contour pixels required in the image quality enhancement algorithm, and]]
[[generate the identified number of sets of the contour pixels to set color information about pixels included in each set,]]
color information about the contour pixels included in at least some of the sets being set to a value representing gray based on a resolution of the first image or specifications of the electronic device (Wang, [Col. 6, Line(s) 61-64]: teaches pixels with a gray color <read on color information>, which are transition pixels forming the border region between the foreground and the background; [Col. 11, Line(s) 23-26]: teaches changing the resolution of the input image <read on first image>).
However, the combination of Wang and Ido does not expressly disclose
identify a number of sets of the contour pixels required in the image quality enhancement algorithm, and
generate the identified number of sets of the contour pixels to set color information about pixels included in each set.
Navasardyan discloses
identify a number of sets of the contour pixels required in the image quality enhancement algorithm (Navasardyan, [0030]: teaches generating a new set of replacement pixel data units <read on identified number of sets of required contour pixels> iteratively; [0032]: teaches performing these iterations until the missing boundaries are exhausted from the missing region of the image data), and
generate the identified number of sets of the contour pixels to set color information about pixels included in each set (Navasardyan, [0030]: teaches iteratively identifying missing boundaries in image data after replacement pixel data units are generated for the current missing boundary, where "a new set of replacement pixel data units are generated for the new missing boundary pixel data units"; [0046]: teaches determining a missing boundary and a missing boundary patch <read on set color information> in a missing region).
Navasardyan is analogous art with respect to Wang, in view of Ido because they are from the same field of endeavor, namely processing and analyzing input images for transparent/missing regions. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to have the system perform iterative identification of missing boundaries and associated missing boundary patches (i.e., textures) in a given image as taught by Navasardyan into the teaching of Wang, in view of Ido. The suggestion for doing so would allow the system to generate new replacement pixel sets in a specific order, thereby allowing for an in-painting process that is coherent and not random. Therefore, it would have been obvious to combine Navasardyan with Wang, in view of Ido.
Regarding Claim 10, the combination of Wang and Ido discloses the electronic device of Claim 1. The combination of Wang and Ido does not expressly disclose the limitations of Claim 10; however, Navasardyan discloses wherein
the pixels adjacent to each pixel include a specified number of pixels surrounding each pixel (Navasardyan, [0053]: teaches "each boundary pixel data unit may be the central pixel data unit of the patch of a specified size <read on specified number of pixels> that includes other pixel data units of the image data contiguously arranged <read on adjacent pixels> around the central pixel data unit").
Navasardyan is analogous art with respect to Wang, in view of Ido because they are from the same field of endeavor, namely processing and analyzing input images for transparent/missing regions. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to have the system perform iterative identification of missing boundaries and associated missing boundary patches (i.e., textures) in a given image as taught by Navasardyan into the teaching of Wang, in view of Ido. The suggestion for doing so would allow the system to generate new replacement pixel sets in a specific order, thereby allowing for an in-painting process that is coherent and not random. Therefore, it would have been obvious to combine Navasardyan with Wang, in view of Ido.
Regarding Claim 20, the combination of Wang and Ido discloses the one or more non-transitory computer-readable storage media of Claim 19. The combination of Wang and Ido does not expressly disclose the limitations of Claim 20; however, Navasardyan discloses
performing, by the electronic device, a function a) of identifying locations of pixels of the transparent region adjacent to pixels included in the first set and having the changed color information (Navasardyan, [0030]: teaches iteratively identifying missing boundaries <read on locating pixels in transparent region> in image data after replacement pixel data units are generated for the current missing boundary);
performing, by the electronic device, a function b) of extracting the pixels whose locations are identified to generate a second set of contour pixels (Navasardyan, [0046]: teaches determining a missing boundary and a missing boundary patch in a missing region <read on location> collection for a given iteration, where "in each iteration, a missing region boundary
∂
M
t
, of the missing region
M
t
, is determined <read on extracting pixels> and is filled"; [0030]: teaches "a new set of replacement pixel data units <read on second set of contour pixels> are generated for the missing boundary pixel data units"); and
performing, by the electronic device, a function c) of setting color information about each pixel included in the second set based on the color information about pixels adjacent to each pixel (Navasardyan, [0030]: teaches iteratively identifying missing boundaries in image data after replacement pixel data units <read on second set> are generated for the current missing boundary, where "a new set of replacement pixel data units are generated for the new missing boundary pixel data units"; [0046]: teaches determining a missing boundary and a missing boundary patch <read on color information> in a missing region), wherein
a specified number of sets of the contour pixels is generated by repeating the function a), the function b), and the function c) to set color information about pixels included in each set (Navasardyan, [0032]: teaches performing an iterative <read on repeating> search for missing boundaries until all missing boundaries are exhausted from the missing region of the image data, where "the number of iterations is limited to a particular number <read on specified number of sets of contour pixels>"), and wherein
an operation of identifying locations of pixels of the transparent region adjacent to a pixel included in a most recently generated set is omitted based on setting color information about the pixel included in the most recently generated set (Navasardyan, [0032]: teaches performing an iterative search for missing boundaries <read on identified locations of pixels of transparent regions> until all missing boundaries are exhausted from the missing region <read on transparent region> of the image data as shown in FIG. 3, where the iterative search processes neighboring pixels; [0030]: teaches a new set of replacement pixel data units are generated <read on most recently generated set> for the new missing boundary pixel data units <read on adjacent pixels>, which is interpreted to be setting color information for each pixel data unit in the new set of replacement pixel data units).
Navasardyan is analogous art with respect to Wang, in view of Ido because they are from the same field of endeavor, namely processing and analyzing input images for transparent/missing regions. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to have the system perform iterative identification of missing boundaries and associated missing boundary patches (i.e., textures) in a given image as taught by Navasardyan into the teaching of Wang, in view of Ido. The suggestion for doing so would allow the system to generate new replacement pixel sets in a specific order, thereby allowing for an in-painting process that is coherent and not random. Therefore, it would have been obvious to combine Navasardyan with Wang, in view of Ido.
Claims 5, 7, 15, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US 8379972 B1), hereinafter referenced as Wang, in view of Ido (US 20190079707 A1) as applied to Claims 4, 1, 14 and 11 above respectively, and further in view of Cragg et al. (US 20200344411 A1), hereinafter referenced as Cragg.
Regarding Claims 5 and 15, the combination of Wang and Ido discloses the electronic device and the method of Claims 4 and 14 respectively. Additionally, Wang further discloses
a display (Wang, [Col. 15, Line(s) 2-3]: teaches display device 960), wherein
[[the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to:display the fourth image on the display in a manner of comparing with the first image.]]
However, the combination of Wang and Ido does not expressly disclose
the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to:display the fourth image on the display in a manner of comparing with the first image.
Cragg discloses
the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to:display the fourth image on the display in a manner of comparing with the first image (Cragg, [0047]: teaches a filter recommendation module analyzing the content of the image <read on first image> for filter recommendations, where a live preview image 106 <read on fourth image> is displayed for comparison).
Cragg is analogous art with respect to Wang, in view of Ido because they are from the same field of endeavor, namely processing and analyzing input images. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to implement a filter recommendation module that analyzes the content of the input image as taught by Cragg into the teaching of Wang, in view of Ido. The suggestion for doing so would offer context to the system and understand what the input image is about, thereby allowing for more accurate and proper filter recommendations. Therefore, it would have been obvious to combine Cragg with Wang, in view of Ido.
Regarding Claims 7 and 17, the combination of Wang and Ido discloses the electronic device and the method of Claims 1 and 11 respectively. Additionally, Wang further discloses
a display (Wang, [Col. 15, Line(s) 2-3]: teaches display device 960), wherein
[[the one or more computer programs further include computer- executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to:analyze the second image to determine the image quality enhancement algorithm corresponding to the second image, and]]
[[display information recommending the image quality enhancement algorithm on the display.]]
However, the combination of Wang and Ido does not expressly disclose
the one or more computer programs further include computer- executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to:analyze the second image to determine the image quality enhancement algorithm corresponding to the second image, and
display information recommending the image quality enhancement algorithm on the display.
Cragg discloses
the one or more computer programs further include computer- executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to:analyze the second image to determine the image quality enhancement algorithm corresponding to the second image (Cragg, [0047]: teaches a filter recommendation module analyzing the content of the image <read on second image> for filter recommendations; [0048]: teaches the system using additional algorithms <read on image quality enhancement algorithm> that are specific to an image category, where a recommended filter and the parameters of the recommended filter are determined), and
display information recommending the image quality enhancement algorithm on the display (Cragg, [0052]: teaches a list of recommended filters <read on displayed information> that can be applied to the current image; [0048]: teaches the system using additional algorithms <read on image quality enhancement algorithm> that are specific to an image category, where a recommended filter and the parameters of the recommended filter are determined).
Cragg is analogous art with respect to Wang, in view of Ido because they are from the same field of endeavor, namely processing and analyzing input images. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to implement a filter recommendation module that analyzes the content of the input image as taught by Cragg into the teaching of Wang, in view of Ido. The suggestion for doing so would offer context to the system and understand what the input image is about, thereby allowing for more accurate and proper filter recommendations. Therefore, it would have been obvious to combine Cragg with Wang, in view of Ido.
Claims 6 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US 8379972 B1), hereinafter referenced as Wang, in view of Ido (US 20190079707 A1), and further in view of Cragg et al. (US 20200344411 A1), hereinafter referenced as Cragg as applied to Claims 5 and 15 above respectively, and further in view of Yang et al. (US 20220415035 A1), hereinafter referenced as Yang.
Regarding Claims 6 and 16, the combination of Wang, Ido, and Cragg discloses the electronic device and the method of Claims 5 and 15 respectively. The combination of Wang, Ido, and Cragg does not expressly disclose the limitations of Claims 6 and 16; however, Yang discloses wherein the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to:
convert and store the fourth image into a specified file format in response to receiving a user input requesting storage of the fourth image (Yang, [0047]: teaches a machine learning model receiving a media file type as input, where the media file type includes information on how it should be encoded <read on specified file format> for computer storage; [0047]: further teaches the machine learning model converting a media file type from one type to another; [0048]: teaches user-inputted images and videos), and wherein
the specified file format includes a file format that is a same file format as a file format of the first image (Yang, [0047]: teaches the machine learning model converting a media file type <read on file format> from one type to another <read on same file format>).
Yang is analogous art with respect to the combination of Wang, Ido, and Cragg because they are from the same field of endeavor, namely processing and analyzing input image files. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to incorporate a machine learning model that is trained to determine what type of media file it receives as input as taught by Yang into the combined teaching of Wang, Ido, and Cragg. The suggestion for doing so would allow the neural network to determine what type of file it has received and convert it from one type to another, thereby yielding predictable results. Therefore, it would have been obvious to combine Yang with the combination of Wang, Ido, and Cragg.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Aydin et al. (US 20210225037 A1) discloses generating a training dataset for training an image matting machine learning model;
Criminisi et al. (US 20040164996 A1) discloses identifying appropriate filling material to replace a destination region in an image;
Price et al. (US 20210256708 A1) discloses a deep neural network based interactive image matting;
Rossato et al. (US 20090154807 A1) discloses determining a subject of an input image/frame from a background region; and
Wilensky et al. (US 20100067786 A1) discloses a digital image that includes first and second regions, which are processed to locate and determine intrinsic colors of given pixels.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KARL TRUONG whose telephone number is (703)756-5915. The examiner can normally be reached 10:30 AM - 7:30 PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kent Chang can be reached at (571) 272-7667. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/K.D.T./Examiner, Art Unit 2614
/KENT W CHANG/Supervisory Patent Examiner, Art Unit 2614
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