Swarm Intelligence Based Fuzzy C-Means Clustering for Motion Vector Selection in Video Watermarking
This work develops a novel video watermarking system in which motion vectors define the locations of watermarks, and the number of watermark bits vary dynamically among frames. Swarm intelligence based Fuzzy C-means (SI-FCM) clustering method is employed to determine the motion vectors and the positions of the watermarks. The proposed scheme has two merits. First, the watermarking strategy does not involve manually setting the location of the watermark bits. Second, the proposed special exclusive-OR operation closely relates the watermark bit to the context of video, preventing attackers from discovering the real watermark length of each frame. Therefore, the proposed approach is highly secure. Video watermarking is achieved using swarm intelligence based FCM clustering which provides a different view from the conventional thresholding method of determining watermark embedding for motion vectors. Experimental results reveal that the watermarked video retains satisfactory quality with very low degradation.
fuzzy c-means motion vector video watermarking swarm intelligence based fcm compressed video