Fast watermarking of MPEG-1/2 streams using compressed-domain perceptual embedding and a generalized correlator detector

A novel technique is proposed for watermarking of MPEG-1 and MPEG-2 compressed video streams. The proposed scheme is applied directly in the domain of MPEG-1 system streams and MPEG-2 program streams (multiplexed streams). Perceptual models are used during the embedding process in order to avoid degradation of the video quality. The watermark is detected without the use of the original video sequence. A modified correlation-based detector is introduced that applies nonlinear preprocessing before correlation. Experimental evaluation demonstrates that the proposed scheme is able to withstand several common attacks. The resulting watermarking system is very fast and therefore suitable for copyright protection of compressed video

Non-noticeable information embedding in color images: marking and detection

One of the problems arising from the use of digital media is the ease of obtaining identical copies of digital images or audio files, allowing manipulation and unauthorized use. Copyright is an effective tool for preserving intellectual property of those documents but authors and publishers need effective techniques preventing copyright modification, due to the straightforward access to multimedia applications and the wider use of digital publications through the WWW. These techniques are generally called watermarking and allow the introduction of side information (i.e. author identification, copyrights, dates, etc.). This work concentrates on the problem of watermarking embedding and optimum detection in color images through the use of spread spectrum techniques, both in space (direct sequence spread spectrum or DSSS) and frequency (frequency hopping). It is applied to RGB and opponent color component representations. Perceptive information is considered in both color systems. Some tests are performed in order to ensure imperceptibility and to assess detection quality of the optimum color detectors.Peer ReviewedPostprint (published version