Most of the existing detection algorithms for testing the region duplication and forgery are not robust in the post region duplication image process,and have high time complexities.In this paper,an efficient and robust algorithm is presented for detecting and localizing this type of malicious forgery.After reducing the image dimension by Discrete Wavelet Transform(DWT),the Zernike moment is applied to the fixed sized overlapping blocks of a low-frequency image in the wavelet sub-band,and the eigenvectors are lexicographically sorted.Then,similar eigenvectors are matched by a certain threshold.Finally,the area threshold is proposed to remove the wrong similar blocks,and the mathematical morphology operations are performed to localize the forgery part.Experimental results show that proposed method is robust and not only can successfully detect this type of forgery for images subjected to post region duplication processing in various forms,but also can search block spaces in only the 1/4 image,which improves the calculation efficiency of algorithm.The method suits to the robust forensics for image contents.