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 .
Response to Amendment
The amendment filed on July 17, 2026, in response to the previous Office Action (04/20/2026) is acknowledged and has been entered.
Claims 1 – 13 are currently pending.
Applicant’s amendment overcomes the following objections/rejections in the last Office Action:
Rejection under 35 U.S.C. 112(b)
Rejection under 35 U.S.C. 101
Objection to Specification
Response to Arguments
Applicant’s arguments with respect to claim(s) have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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) 1 – 4, 7 – 10, 12 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Li (US 2009/0147098) in view of Gill (US 2009/0268044).
Regarding claim 1, Li discloses a method for providing color correction for a specific camera sensor, comprising: providing a reference image, wherein the reference image results from a capture of the specific camera sensor, the reference image comprises raw, color-filtered data arranged according to a Bayer pattern, such that each pixel of the reference image has a value corresponding to only one of red, green, and blue (fig. 3, ¶47); performing a color interpolation of the reference image to generate an interpolated image in which each pixel has color values for red, green, and blue, wherein the color interpolation estimates missing color values for each pixel based on color values of neighboring pixels (¶41: demosaic); determining at least one respective area of interest for the colors red, green and blue in the interpolated image (whole image/scene); forming an average of color values in each determined area of interest to obtain a respective resulting average color (¶48: white balance); generating a color correction matrix based on color values of the reference image (fig. 3; ¶48-50); calculating a respective intermediate variable for the colors red, green and blue based on the generated color correction matrix (fig. 3; ¶48-50); and minimizing a respective difference for the colors red, green and blue between the color values of the reference image and the respective intermediate variable calculated to provide the color correction for the specific camera sensor (fig. 3; ¶48-50). Li fails to explicitly disclose forming an average of color values in each determined area of interest to obtain a respective resulting average color and then assigning a respective reference color to each resulting average color, wherein the reference colors comprise at least the colors red, green and blue.
In a similar field of endeavor, Gill teaches color correcting an image based on a plurality of matrices, wherein the image signal processing correction system or module 50 further comprises a look-up table (LUT), such as a hashed LUT 56 for storing a plurality of base matrices M.sub.j's so that the color correction matrix M can be computed for color correction when needed; and whenever a user takes a picture, the image data of the picture is white balanced and color corrected, and the color correction matrix M is derived, based on the stored M.sub.j's, for each set of color coordinates (r, g, b) in the white-balanced image data (¶28, 31). In light of the teaching of Ishii, it would have been obvious, before the effective filing date, to one of ordinary skill in the art to use Ishii’s teaching in Bhatti’s system because an artisan of ordinarily skill would recognize that this would result in overall image optimization and minimize the difference between target color values and input image values.
Regarding claim 2, Li in view of Gill disclose the limitations of claim 1. Gill also teaches further comprising: rendering the interpolated image in order to determine the at least one respective area of interest based on the rendered interpolated image (¶2, 28: image processed before display).
Regarding claim 3, Li view of Gill disclose the limitations of claim 1. Bhatti also teaches wherein the assigning step comprises: creating a table, wherein the table comprises a respective assignment of the reference colors to the resulting average colors (¶28, 31).
Regarding claim 4, Li in view of Gill disclose the limitations of claim 1. Li also teaches wherein: generating the color correction matrix is performed using a non-integer equation solver, and three variables are generated for each color (¶48-50).
Regarding claim 7, Li in view of Gill disclose the limitations of claim 1. Li also teaches further comprising: determining the color values of the reference image based on an analysis of the reference image (fig. 1; ¶35-38, 47).
Regarding claim 8, Li in view of Gill disclose the limitations of claim 1. Li also teaches wherein a computer program comprises commands for causing a computer to carry out the method when the computer program is executed by the computer (see rejection of claim 1; ¶16).
Claims 9 – 10 rejected for the same reasons as claim 8.
Regarding claim 12, Li in view of Gill disclose the limitations of claim 1. Li also teaches wherein: generating the color correction matrix comprises generating nine variables arranged as a 3x3 matrix, and each row of the 3x3 matrix represents a corresponding one of a red channel, a green channel, and a blue channel of the interpolated image (fig. 1; ¶48-50).
Claim(s) 5 are rejected under 35 U.S.C. 103 as being unpatentable over Li in view of Gill in view of Ishii (US 2013/0057714).
Regarding claim 5, Li in view of Gill disclose the limitations of claim 4 but fails to explicitly disclose wherein the non-integer equation solver is an advanced process optimizer or an interior point optimizer.
In a similar field of endeavor, Ishii teaches image capture device that uses interior point optimization method for overall image optimization (¶121). In light of the teaching of Ishii, it would have been obvious, before the effective filing date, to one of ordinary skill in the art to use Ishii’s teaching in Li’s system because an artisan of ordinarily skill would recognize that this would result in overall image optimization and minimize the difference between target color values and input image values.
Claim(s) 6 are rejected under 35 U.S.C. 103 as being unpatentable over Li in view of Gill in view of Zhang (US 2013/0093915).
Regarding claim 6, Li in view of Gill disclose the limitations of claim 4 but fails to explicitly disclose wherein the non-integer equation solver is configured to perform a breadth-first search in a nonlinear programming mode.
In a similar field of endeavor, Zhang teaches an image processing method for implementing a more effective CCM coefficient determination approach based on an estimated scene white point (¶9) using optimization algorithms including BFS (¶21-39. In light of the teaching of Zhang, it would have been obvious, before the effective filing date, to one of ordinary skill in the art to use Zhang’s teaching in Li’s system because an artisan of ordinarily skill would recognize that this would result in improved approximation and interpolation of color correction matrices.
Claim(s) 11 are rejected under 35 U.S.C. 103 as being unpatentable over Li in view of Gill in view of Xu (D. Xu, S. Boussakta and J. P. Bentley, "An FPGA-based low-cost frame grabber for image processing applications," ICECS 2000. 7th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.00EX445), Jounieh, Lebanon, 2000, pp. 333-336 vol.1, doi: 10.1109/ICECS.2000.911549.).
Regarding claim 11, Li in view of Gill disclose the limitations of claim 1 but fails to explicitly disclose wherein the reference image is captured using an FPGA-based frame grabber.
In a similar field of endeavor, Xu teaches a low-cost frame grabber, which was specifically designed as part of a real-time motion detection system for high-resolution image (abstract). In light of the teaching of Xu, it would have been obvious, before the effective filing date, to one of ordinary skill in the art to use Xu’s teaching in Li’s system because an artisan of ordinarily skill would recognize that this would result in minimizing the size of a PCB, thus minimizing the device while capturing clear frames.
Claim(s) 13 are rejected under 35 U.S.C. 103 as being unpatentable over Li in view of Gill in view of Lee (US 2022/0150453).
Regarding claim 13, Li in view of Gill disclose the limitations of claim 1 but fails to explicitly disclose wherein: the specific camera sensor is a camera sensor of a camera of a vehicle, and the color correction is provided for image processing used by a vehicle device configured to provide an autonomous driving function or a driver assistance system.
In a similar field of endeavor, Lee teaches an imaging device that color corrects images using CCMs, wherein the device may be applied to a vehicle 3800 and used to provide information necessary for autonomous driving (fig. 1, 30, 31, 52; ¶11, 349. In light of the teaching of Lee, it would have been obvious, before the effective filing date, to one of ordinary skill in the art to use Lee’s teaching in Li’s system because an artisan of ordinarily skill would recognize that this would result in the vehicle providing a variety of information about the interior or surroundings of the vehicle to a driver and may automatically recognize objects or people in the image to provide information necessary for autonomous driving.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANTOINETTE SPINKS whose telephone number is (571)270-3749. The examiner can normally be reached M-Th 7am - 5pm EST.
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/ANTOINETTE T SPINKS/Primary Examiner, Art Unit 2639
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