Abstract: Aiming at the problem that the classification features selected by the existing blind identification algorithms of photorealistic computer graphics have high dimensions and poor universalities,this paper put forward a blind identification algorithm of photorealistic computer graphics based on local binary count.First,the original image is converted from RGB color space to HSV color space.Then,the local binary count matrix is extracted from the HSV color space images and its down-sampling image,and the normalized histogram of the matrix is calculated.Finally,the above histogram is sent as classification features into the SVM classifier,implementing the blind identification of photorealistic computer graphics.The experimental results show that the algorithm can effectively identify photographic images and photorealistic computer graphics.Compared with the existing algorithm,it has higher recognition rate and lower feature dimension.

Key words: Blind identification,Photorealistic computer graphics,Down-sampling image,Local binary count,SVM classifier