Self-Recovery Algorithm Based on Motion Estimation of I-Frames for Compressed Video

Abstract

Self-recovery watermarking has the ability to recover the tampered host data at the absence of any other additional information, and it plays an important role in the multimedia content authentication. Since self-recovery schemes often need a large amount of data, they have disadvantages in imperceptibility, and the embedded data is easy to be destroyed. In this paper, a novel self-recovery algorithm named MEI (Motion Estimation of I-Frames) is proposed for the authentication of video. MEI applies motion estimation scheme to adjacent I-frames and uses prediction errors as well as motion vectors to generate recovery watermark. GOP mapping and area mutex strategies are utilized to select the embedding position when the recovery watermark is embedded into P-frames. Experimental results have demonstrated that, with MEI algorithm, the data volume of self-recovery is decreased considerably, which is significant for reducing the distortion of watermarked video and achieving better security for embedded data. MEI also improves the visual quality of recovered frames in the video.