A video forgery detection algorithm based on compressive sensing

Video processing software is often used to delete moving objects and modify the forged regions with the information provided by the areas around them. However, few algorithms have been suggested for detecting this form of tampering. In this paper, a novel algorithm based on compressive sensing is proposed for the detection in which the moving foreground was removed from background. Firstly, the features of the difference between frames are obtained through K-SVD (k-Singular Value Decomposition), and then random projection is used to project the features into the lower-dimensional subspace which is clustered by k-means, and finally the detection results are combined to output. The experimental results show that our algorithm has higher detection accuracy and better robustness than that of the previous algorithms.

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