DETAILED ACTION
Preliminary Remarks
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
This application is a continuation of PCT/JP2022/022229 filed 05/31/22 which is claims priority of JP 2021-141805 filed 08/31/21.
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.
Claim(s) 1-13 and 15-17 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Vaughn (U.S. Publication 2004/0021784).
In reference to claim 1, Vaughn discloses a data generation method of generating first image data which is image data obtained by imaging a subject via an imaging apparatus and which includes accessory information (see paragraphs 9, 19-22, 26-27, 39 and Figures 1 and 5 wherein Vaughn discloses a method of improving a digital image captured by a digital camera. Vaughn discloses the method utilizing a digital camera which comprises of at least one processor and that produces digital images using an image sensor. Vaughn discloses the digital camera comprising an image processor that performs color processing upon the image data utilizing regression processing of color chart data forming either profile or color matrix type data of which the Examiner interprets functionally equivalent to Applicant’s “accessory information.”), the data generation method comprising:
a first generation step and a second generation step (see paragraphs 19, 27, 39 and #500, 502, 505 of Figure 5 wherein Vaughn discloses capturing and analyzing an image of a color chart and then through a regression procedure deriving a color correction matrix or profile.),
wherein the image data is used in machine learning (see paragraphs 19, 27, 39 and #502-504 of Figure 5 wherein Vaughn discloses utilizing the color chart in a regression procedure which utilizes captured color patch data with reference color patch data to produce either an ICC profile or a color matrix that colorimetrically balances the image for that set of conditions that the images are captured under. Note, the Examiner interprets such regression procedure in Vaughn functionally equivalent to a “machine learning” since it learns a mapping from data. Thus taking the broadest definition of “machine learning” as any data-driven model for improvement of a task, the techniques of Vaughn can surely be considered equivalent thereto.),
the first generation step generating the first image data by performing first image processing via the imaging apparatus (see paragraphs 19, 27 and 39 wherein Vaughn explicitly discloses the digital camera capturing and analyzing an image of a color chart under the illuminant or in the venue used to capture subsequent images.); and
the second generation step generating first information based on image processing information related to the first image processing, as information included in the accessory information (see paragraphs 19, 27, 39 and #502-504 of Figure 5 wherein Vaughn discloses utilizing the color chart in a regression procedure which utilizes captured color patch data with reference color patch data to produce either an ICC profile or a color matrix that colorimetrically balances the image for that set of conditions that the images are captured under.).
In reference to claims 2 and 16, Vaughn discloses all of the claim limitations as applied to claims 1 and 15 respectively. Vaughn explicitly discloses the digital camera capturing an image of a color chart under the illuminant or in the venue used to capture subsequent images (see paragraphs 19, 27 and 39 and Figure 2).
In reference to claim 3, Vaughn discloses all of the claim limitations as applied to claim 2 above. Vaughn explicitly discloses the digital camera capturing an image of a color chart under the illuminant or in the venue used to capture subsequent images (see paragraphs 19, 27 and 39 and Figure 2). Vaughn discloses capturing color patches from the color chart (see paragraph 27 and Figure 2).
In reference to claim 4, Vaughn discloses all of the claim limitations as applied to claim 2 above. Vaughn discloses utilizing the captured color patch data with reference color patch data (see paragraph 27) which either of, can be interpreted as “stored in advance” as there lacks any sort of basis as to compare “timing” to such data therefore allowing for a broadest interpretation of the term to one of ordinary skill in the art.
In reference to claims 5-7, Vaughn discloses all of the claim limitations as applied to claim 2 above. Vaughn discloses capturing color patches from the color chart (see paragraph 27 and Figure 2). Since Vaughn explicitly discloses the patch data comprising red, green, blue channel information, the Examiner interprets that least “one or two of chroma saturation, lightness or hue” are represented thereby (see paragraphs 29-34, 39 and Figure 2). Further, one of ordinary skill in the art would surely find equivalent the color patch red, green and blue channel information equivalent to Applicant’s “one or two of the first signal value, the second signal value or the third signal value are different between the plurality of color patches, and the rest are the same.”
In reference to claim 8, Vaughn discloses all of the claim limitations as applied to claim 2 above. Vaughn explicitly discloses the digital camera capturing an image of a color chart under the illuminant or in the venue used to capture subsequent images (see paragraphs 19, 27 and 39 and Figure 2). Vaughn discloses utilizing the captured color patch data with reference color patch data (see paragraph 27) which the Examiner interprets as at least inherently being “color chart data” from “a reference imaging apparatus.”
In reference to claims 9 and 10, Vaughn discloses all of the claim limitations as applied to claim 2 above. Vaughn explicitly discloses the digital camera capturing an image of a color chart under the illuminant or in the venue used to capture subsequent images (see paragraphs 19, 27 and 39 and Figure 2). Vaughn explicitly discloses the patch data comprising red, green, blue channel information (see paragraphs 29-34, 39 and Figure 2) therefore, the Examiner interprets that the color chart information generated is at least inherently based on spectral characteristics of the imaging apparatus and chart colors themselves.
In reference to claim 11, Vaughn discloses all of the claim limitations as applied to claim 2 above. Vaughn discloses further performing a color correction matrix or profile creation process utilizing the regression processed data (see paragraph 39 and #504 of Figure 5). Vaughn discloses utilizing such data to apply corrections for subsequently captured images (see paragraphs 20, 26 and 27).
In reference to claim 12, Vaughn discloses all of the claim limitations as applied to claim 1 above. Vaughn discloses further performing a color correction matrix or profile creation process utilizing the regression processed data (see paragraph 39 and #504 of Figure 5).
In reference to claim 13, Vaughn discloses all of the claim limitations as applied to claim 1 above. Vaughn further explicitly discloses performing white balance correction based upon the color chart information and a specific middle gray patch from the chart whereby a gain for each red, green, blue color channel is computed (see paragraphs 29-35).
In reference to claim 15, claim 15 is similar in scope to claim 1 and is therefore rejected under like rationale. In addition to the rationale as applied in the rejection of claim 1 above, claim 15 further recites, “An imaging apparatus comprising: n image sensor; and a processor….” Vaughn discloses the camera comprising an image such as for example a CCD image sensor (see at least paragraph 19). Vaughn discloses the method utilizing a digital camera which comprises of at least one processor and that produces digital images using an image sensor (see paragraphs 19, 22 and #62, 66 of Figure 1).
In reference to claim 17, claim 17 is similar in scope to claim 1 and is therefore rejected under like rationale. In addition to the rationale as applied in the rejection of claim 1 above, claim 17 further recites, “A non-transitory computer-readable storage medium storing a program executable by a computer to perform…” Vaughn discloses the method utilizing a digital camera which comprises of at least one processor and that produces digital images using an image sensor (see paragraphs 19, 22 and #62, 66 of Figure 1). Vaughn discloses the at least one processor performing processing to execute the invention as determined by firmware stored in a firmware memory such as an EPROM memory (see paragraph 20 and #66, 70 of Figure 1).
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.
Claim(s) 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vaughn (U.S. Publication 2004/0021784).
In reference to claim 14, Vaughn discloses all of the claim limitations as applied to claim 11 above. Although Vaughn discloses capturing color chart data via a digital camera, utilizing reference color chart data to perform a regression and output corrected color matrix/profile information Vaughn does not explicitly disclose performing a learning method executing machine learning using images subsequently captured via the corrected processed color data. It is well known in the art of image processing to perform color correction and processing techniques utilizing machine learned techniques. Adopting machine learning as a superior alternative to conventional image processing techniques offers improved accuracy, adaptability, and automation while building directly on known data acquisition methods (Official Notice). It would have been obvious to one of ordinary skill in the art for Vaughn who already teaches performing image capturing techniques utilizing captured color data, to use machine-learned techniques in the process because adopting machine learning as a superior alternative to conventional image processing techniques offers improved accuracy, adaptability, and automation.
Response to Arguments
Applicant's arguments filed 12/29/25 have been fully considered but they are not persuasive.
In reference to claims 1-17, Applicant argues the 35 USC 102 & 103 rejections based upon primary reference Vaughn and particularly argues that 1) the first image data itself includes accessory information and 2) data inclusion in which first information based on image processing information related to the first image processing is include in the accessory information (see page 6 of Applicant’s Remarks). Further, Applicant contends that Vaughn solely described that the profile or matrix data is stored on the imaging apparatus and not within image data (see pages 7 & 8 of Applicant’s Remarks). Additionally, Applicant argues that the image data is “used in machine learning” which is now in the body of the claim and of which Vaughn does not disclose (see pages 7-8 of Applicant’s Remarks).
In response, the Examiner disagrees. Firstly, the Examiner states the techniques of Vaughn perform a regression procedure upon the image data (see at least paragraph 39) of which the Examiner interprets, when broadly taking the definition of “machine learning,” functionally equivalent to thereto. The “learning” in Vaughn is performed via the regression procedure as it develops associations from data for improvement of a task, e.g. color corrections in image data. Even so, the claimed “used in” type language is merely descriptive and does not define the inventive concept. This language simply states a potential application of the generated image data instead of providing a concrete element/step in a process/device. Secondly, Applicant desires the claim to explicitly teach the “accessory information” being stored or comprised within the image data however, this is not the case. None of the claims explicitly or implicitly disclose any type of language that “stores” “saves” “configures” the “accessory information” within the image data. The claims, in particular independent claims, solely recite generating first information as information included in the accessory information while the preamble (claims 1 and 17, for example) simply states, “a data generation method of generating first image data…and which includes accessory information…” In this passage, it is unclear as to what the “includes” refers to as the preamble, “the data generation method” is simply being defined as performing the accessory information derivation. Claim 15 states, “…as information included in accessory information of the first image data…” None of the language explicitly or implicitly states that the accessory information is stored, saved, configured within the image data. The term “of the first image data” cannot be interpreted, to one of ordinary skill in the art to even infer such. In contrast, the specification explicitly details such “accessory information” as “metadata” (see paragraph 11 of Applicant’s specification) (also mentioned by Applicant’s Remarks, see page 7) as its association with the image data of which is commonly known to be stored with image data. However, in response to Applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which Applicant relies are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
In view of such rationale, the Examiner deems the rejection of the claims based upon at least Vaughn as just.
Conclusion
THIS ACTION IS MADE FINAL. 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Antonio Caschera whose telephone number is (571) 272-7781. The examiner can normally be reached Monday-Friday between 6:30 AM and 2:30 PM EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Said Broome, can be reached at (571) 272-2931.
Any response to this action should be mailed to:
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P.O. Box 1450
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or faxed to:
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Any inquiry of a general nature or relating to the status of this application or proceeding should be directed to the Technology Center 2600 Customer Service Office whose telephone number is (571) 272-2600.
/Antonio A Caschera/
Primary Examiner, Art Unit 2612
2/25/26