Adaptive Video Watermarking Utilizing Video Characteristics in 3D-DCT Domain

Abstract

In this paper, we propose an adaptive blind video watermarking method using video characteristics based on human visual system (HVS) in three-dimensional discrete cosine transform (3D-DCT) domain. In order to optimize the weight factors for watermarking, we classify the patterns of 3D-DCT cubes and the types of video segments by using the texture and motion information of 3D-DCT cubes. Then we embed an optimal watermark into the mid-range coefficients of 3D-DCT cubes by using the trained optimal weight factors. Experimental results show that the proposed method achieves better performance in terms of invisibility and robustness than the previous method under the various possible attacks such as MPEG compression, frame dropping, frame insertion and frame swapping to experimental videos.