Copy and paste tampering forensics algorithm based on C-SIFT feature vector image
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TN911.73

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    Abstract:

    Nowadays, the network era is full of tamper-evident images. At present, the detection method such as local invariant characterization and the Harris corner algorithm has low accuracy in copying and pasting tampering. In this paper, a complete grayscale partial image is obtained by color image segmentation, color space edged extraction, and image grayscale. By extracting, marking, matching and normalizing the feature vector set in different image blocks, the feature vector is successfully matched after the Euclidean distance reaches a certain threshold, that is, the image has the trace of copying and pasting tampering. Finally, three different types of photo simulation tests are selected, which shows that the algorithm can effectively improve the detection success rate and detection rate of copying and pasting tampering images.

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  • Received:
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  • Online: July 29,2021
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