Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: RST-Resilient Video Watermarking Using Scene-Based Feature Extraction | EURASIP Journal on Applied Signal Processing 2004 14 2113-2131 2004 Hindawi Publishing Corporation RST-Resilient Video Watermarking Using Scene-Based Feature Extraction Han-Seung Jung School of Electrical Engineering and Computer Science Seoul National University San 56-1 Sillim-Dong Gwanak-gu Seoul 151-742 Korea Email jhs@ Young-Yoon Lee School of Electrical Engineering and Computer Science Seoul National University San 56-1 Sillim-Dong Gwanak-gu Seoul 151-742 Korea Email yylee@ Sang Uk Lee School of Electrical Engineering and Computer Science Seoul National University San 56-1 Sillim-Dong Gwanak-gu Seoul 151-742 Korea Email sanguk@ Received 31 March 2003 Revised 5 April 2004 Watermarking for video sequences should consider additional attacks such as frame averaging frame-rate change frame shuffling or collusion attacks as well as those of still images. Also since video is a sequence of analogous images video watermarking is subject to interframe collusion. In order to cope with these attacks we propose a scene-based temporal watermarking algorithm. In each scene segmented by scene-change detection schemes a watermark is embedded temporally to one-dimensional projection vectors of the log-polar map which is generated from the DFT of a two-dimensional feature matrix. Here each column vector of the feature matrix represents each frame and consists of radial projections of the DFT of the frame. Inverse mapping from the one-dimensional watermarked vector to the feature matrix has a unique optimal solution which can be derived by a constrained least-square approach. Through intensive computer simulations it is shown that the proposed scheme provides robustness against transcoding including frame-rate change frame averaging as well as interframe collusion attacks. Keywords and phrases scene-based video watermarking RST-resilient radial projections of the DFT feature extraction inverse feature extraction least-square optimization .
