Zernike Moment-Based Spatial Image Steganography Resisting Scaling Attack and Statistic Detection

Abstract

The mainstream adaptive steganography algorithm is difficult to resist scaling attack, and the anti-detection performance of the algorithm based on quantization index modulation is not high enough. To solve the above problems, this paper proposes a spatial image adaptive steganography algorithm based on Zernike moment to resist scaling attack and statistic detection. First, the Zernike moment of the normalized cover image is extracted and the new cover is obtained by the dither modulation algorithm. Second, the minimized distortion embedding is realized by Spatial UNIversal WAvelet Relative Distortion (S-UNIWARD) and syndrome-trellis codes coded. And finally, the stego image is generated by changing the original Zernike moment according to the modified amplitude of the new cover. The experimental results show that the proposed algorithm is robust to the three common scaling attacks, and the message extraction error rate is significantly lower than the S-UNIWARD steganography after the scaling attacks; moreover, compared with the steganography algorithm based on quantization index modulation, the proposed algorithm has higher detection resistance.