Video dual watermarking algorithm against geometric attack based on ASIFT and contourlet transform

This study proposed a video dual watermarking algorithm based on affine-scale invariant feature transform (ASIFT) and contourlet transform. First, the human visual masking model of a 3D motion in video sequence is studied in depth. The human eye visual masking threshold is obtained as the maximum embedding intensity of watermark using various motion characteristics. Second, the high- and low-frequency sub-band coefficients of the contourlet field are obtained by contourlet transform. Chaotic watermarking sequence is embedded into the high-frequency sub-band coefficient with the highest energy to increase imperceptibility. Third, when the low-frequency sub-band coefficients has the stability of its coefficient histogram against geometric attacks such as rotation and scaling, the watermark signal is embedded in a low-frequency sub-band histogram of adjacent coefficients to increase the watermark of an anti-geometric attack. Finally, ASIFT is used as a trigger to determine whether the video frame is subjected to geometric attacks or not. For geometric distortions, ASIFT is used to regulate the geometrically attacked video frame. The low-frequency sub-band coefficients of the regulated video frame are used for the watermarking extraction algorithm. The high-frequency watermarking extraction algorithm is used directly for the non-geometric distortions. Experimental results show that the proposed algorithm could guarantee watermark invisibility and favorably extract the watermark for common geometric and conventional signal attacks. The proposed algorithm is a strong video-dual watermarking algorithm.