Robust semi-blind video watermarking based on frame-patch matching

In this paper, we present a frame-patch matching based robust semi-blind video watermarking using KAZE feature. The KAZE feature is employed for matching the feature points of frame-patch with those of all frames in video for detecting the embedding and extracting regions. In our method, the watermark information is embedded in Discrete Cosine Transform (DCT) domain of randomly generated blocks in the matched region. In the extraction process, we synchronize the embedded region from the distorted video by using KAZE feature matching. Based on the matched KAZE feature points, RST (rotation, scaling, translation) parameters are estimated and the watermark information can be successfully extracted. Experimental results show that our proposed method is robust against geometrical attacks, video processing attacks, temporal attacks, and so on.