# US 10,373,341 B2 · Systems and methods for automated color correction > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,373,341 B2 - Document ID: US10373341B2 - Status: Granted - Kind: B2 - Application number: 15/688,006 - Filed: 2017-08-28 - Published: 2019-02-28 - Granted: 2019-08-06 - Earliest claimed: 2017-08-28 - Assignees: Facebook, Inc. - Applicants: Facebook, Inc. - Inventors: Ittai M. Golde - Web page: https://patentgrep.com/patent/US10373341B2 ## CPC - G06T 7/90: Determination of colour characteristics - G06N 20/00: Machine learning - G06T 11/10: Texturing; Colouring; Generation of textures or colours (retouching, inpainting or scratch removal G06T5/77) - H04N 1/6008: {with primary colour signals, e.g. RGB or CMY(K)} - H04N 1/603: {controlled by characteristics of the picture signal generator or the picture reproducer} - G06N 5/022: Knowledge engineering; Knowledge acquisition - G06T 2200/24: involving graphical user interfaces [GUIs] - G06T 2207/10024: Color image - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract Systems, methods, and non-transitory computer-readable media can identify an object depicted in an image. True color information associated with the object is obtained from a true color database comprising true color information for a plurality of objects. A color delta associated with the object is determined based on the true color information and captured color information associated with the object. The image is modified based on the color delta. ## Claims ### Claim 1 A computer-implemented method comprising: identifying, by a computing system, an object depicted in an image; obtaining, by the computing system, true color information associated with the object from a true color database, the true color database comprising true color information for a plurality of objects; determining, by the computing system, a color delta associated with the object based on the true color information and captured color information associated with the object; and modifying, by the computing system, the image based on the color delta. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein the identifying the object depicted in the image is performed automatically based on one or more machine learning models. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein the true color information comprises a true color RGB value, and the captured color information comprises a captured color RGB value. ### Claim 4 (depends on 3) The computer-implemented method of claim 3, wherein the color delta comprises a difference of the true color RGB value and the captured color RGB value. ### Claim 5 (depends on 4) The computer-implemented method of claim 4, wherein the modifying the image based on the color delta comprises applying the color delta to each pixel in the image. ### Claim 6 (depends on 3) The computer-implemented method of claim 3, wherein the true color information associated with the object comprises a plurality of RGB values, and further wherein the plurality of RGB values are indicative of the object containing a plurality of colors. ### Claim 7 (depends on 3) The computer-implemented method of claim 3, wherein the captured color information associated with the object comprises an average of a plurality of pixel RGB values for a plurality of pixels associated with the object. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, wherein the identifying the object depicted in the image is performed based on user identification of one or more objects in the image. ### Claim 9 (depends on 1) The computer-implemented method of claim 1 further comprising: identifying a second object depicted in the image; and determining that the second object is not associated with true color information in the true color database. ### Claim 10 (depends on 1) The computer-implemented method of claim 1 further comprising: identifying a second object depicted in the image; obtaining true color information associated with the second object from the true color database; and calculating a second color delta associated with the second object based on the true color information associated with the second object and captured color information associated with the second object, wherein the modifying the image comprises modifying the image based on the color delta and the second color delta. ### Claim 11 A system comprising: at least one processor; and a memory storing instructions that, when executed by the at least one processor, cause the system to perform a method comprising: identifying an object depicted in an image; obtaining true color information associated with the object from a true color database, the true color database comprising true color information for a plurality of objects; determining a color delta associated with the object based on the true color information and captured color information associated with the object; and modifying the image based on the color delta. ### Claim 12 (depends on 11) The system of claim 11, wherein the identifying the object depicted in the image is performed automatically based on one or more machine learning models. ### Claim 13 (depends on 11) The system of claim 11, wherein the true color information comprises a true color RGB value, and the captured color information comprises a captured color RGB value. ### Claim 14 (depends on 13) The system of claim 13, wherein the color delta comprises a difference of the true color RGB value and the captured color RGB value. ### Claim 15 (depends on 14) The system of claim 14, wherein the modifying the image based on the color delta comprises applying the color delta to each pixel in the image. ### Claim 16 A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform a method comprising: identifying an object depicted in an image; obtaining true color information associated with the object from a true color database, the true color database comprising true color information for a plurality of objects; determining a color delta associated with the object based on the true color information and captured color information associated with the object; and modifying the image based on the color delta. ### Claim 17 (depends on 16) The non-transitory computer-readable storage medium of claim 16, wherein the identifying the object depicted in the image is performed automatically based on one or more machine learning models. ### Claim 18 (depends on 16) The non-transitory computer-readable storage medium of claim 16, wherein the true color information comprises a true color RGB value, and the captured color information comprises a captured color RGB value. ### Claim 19 (depends on 18) The non-transitory computer-readable storage medium of claim 18, wherein the color delta comprises a difference of the true color RGB value and the captured color RGB value. ### Claim 20 (depends on 19) The non-transitory computer-readable storage medium of claim 19, wherein the modifying the image based on the color delta comprises applying the color delta to each pixel in the image.