Image Forgery Detection Algorithm Based on Non-Sampling Wavelet Transform and Zernike Moments
نویسنده
چکیده
The image forgery detection technology based on non sampling wavelet transform coupling with Zernike moments is proposed in this article. Specifically, LL and HH sub-bands are obtained through non sampling wavelet transform to calculate the similarity and the diversity of the image blocks, and then LL similarity and HH diversity are combined for dual judgment. Meanwhile, Zernike moments are introduced therein to construct distance matrix for image feature matching. Finally, the images are selected from CASIA TIDEV1.0 database for algorithm evaluation, and the experimental result shows: the algorithm proposed in the article has the features of good noise immunity, good compression resistance, high algorithm accuracy, low false negative rate and low false positive rate.
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