Earticle

In order to solve such problems as poor robustness and low detection accuracy in the present copying & pasting forgery detection algorithm, an image copying & moving forgery detection algorithm based on non-sampling wavelet transform (undecimated wavelet transform, UWT) coupling with Zernike moments is proposed in this article. Firstly, the non-sampling wavelet transform is adopted to decompose the input image into approximation coefficient LL and detail coefficient HH to obtain the similarity and the diversity of the image blocks; secondly, the overlapped blocks are divided to calculate the sub-block interval of the image; thirdly, the sub-blocks are ordered and classified according to LL similarity and HH diversity; fourthly, Zernike moments are introduced to construct the distance matrix for image feature matching and image forgery detection. The experiment shows: the algorithm proposed thereby has good translation invariance and amplitude rotation invariance, good post-processing resistance performance, high detection accuracy, low false negative rate and low false positive rate.