In the paper, an effective method for reducing Geometrical Error (G.E) and Numerical Error (N.E) of Zernike moments is proposed. By running MATLAB for the proposed Zernike's algorithm, the results of our proposed methods have shown a remarkable improvement to the total error of the analysis. The new proposed technique in reducing significantly Geometrical Error is performed better than that in the traditional technique. Considering two sides of G.E, N.E minimization and the reconstructed images having their size are almost with unchanged forms compared to the original images, then the proposed method has proven its potential capability in significantly reducing the two main errors of Zernike moments computation. Finally, the copy-move-rotate detection program has written by C++ under supporting OpenCV and Boost libraries that helps to verify the authentication of images. Index Terms-tampered image detection, Zernike polynomial, geometric moments, region of interest Manuscript
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