US 12,488,567 B2
Image authenticity detection method and apparatus
Zhou Han, Guangdong (CN); Zhuang Zhang, Guangdong (CN); and Zhiqiang Dong, Guangdong (CN)
Assigned to Tencent Technology (Shenzhen) Company Limited, (CN)
Filed by Tencent Technology (Shenzhen) Company Limited, Guangdong (CN)
Filed on Nov. 3, 2022, as Appl. No. 17/979,883.
Application 17/979,883 is a continuation of application No. PCT/CN2022/085430, filed on Apr. 7, 2022.
Claims priority of application No. 202110512723.X (CN), filed on May 11, 2021.
Prior Publication US 2023/0056564 A1, Feb. 23, 2023
Int. Cl. G06F 21/30 (2013.01); G06T 5/70 (2024.01); G06V 10/74 (2022.01); G06V 10/771 (2022.01)
CPC G06V 10/771 (2022.01) [G06F 21/30 (2013.01); G06T 5/70 (2024.01); G06V 10/761 (2022.01)] 19 Claims
OG exemplary drawing
 
1. An image authenticity detection method, performed by a computer device, comprising:
obtaining an image;
removing low-frequency information from the image to obtain first image information of the image;
denoising the first image information to obtain second image information;
determining, based on a difference between the first image information and the second image information, a fixed pattern noise feature map corresponding to the image;
analyzing distribution of fixed pattern noise in the fixed pattern noise feature map, the fixed pattern noise being inherent noise from a camera sensor and not interfered by image content; and
detecting, based on the distribution of fixed pattern noise in the fixed pattern noise feature map, authenticity of the image to obtain an authenticity detection result of the image, the authenticity detection result including that the image is an authentic image or the image is a forged image, wherein the detecting further comprises in response to the distribution matching fixed pattern noise distribution of a preset forgery type, determining the image to be a forged image of the forgery type based on the forgery type corresponding to the matched fixed pattern noise distribution, the forgery type comprises at least one of a type of tampering, a type of synthesis, or a type of artificial intelligence generation.