US 11,836,634 B2
Detecting digital image manipulations
Lakshmanan Nataraj, Chennai (IN); Tajuddin Manhar Mohammed, Goleta, CA (US); Tejaswi Nanjundaswamy, San Jose, CA (US); Michael Gene Goebel, Santa Barbara, CA (US); Bangalore S. Manjunath, Santa Barbara, CA (US); and Shivkumar Chandrasekaran, Santa Barbara, CA (US)
Assigned to Mayachitra, Inc., Santa Barbara, CA (US)
Filed by Mayachitra, Inc., Santa Barbara, CA (US)
Filed on Jun. 7, 2022, as Appl. No. 17/834,455.
Application 17/834,455 is a continuation of application No. 16/801,866, filed on Feb. 26, 2020, granted, now 11,429,812.
Claims priority of provisional application 62/956,999, filed on Jan. 3, 2020.
Prior Publication US 2022/0318569 A1, Oct. 6, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 3/08 (2023.01); G06N 3/088 (2023.01); G06F 18/214 (2023.01); G06F 18/21 (2023.01); G06N 3/045 (2023.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 10/44 (2022.01)
CPC G06N 3/088 (2013.01) [G06F 18/217 (2023.01); G06F 18/2148 (2023.01); G06N 3/045 (2023.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving, using one or more processors, an image that comprises a plurality of color channels;
generating, using the one or more processors, a plurality of co-occurrence matrices on pixel values of the plurality of color channels of the image;
generating, using the one or more processors, analysis of the image based on the generated plurality of co-occurrence matrices using a convolutional neural network trained to detect images that are generated using a generative adversarial network (GAN); and
classifying, using the one or more processors, the image as an authentic image based on the analysis.