Digital watermarking can be used to protect the intellectual property for multimedia data. In this paper, we introduce an image watermarking scheme based on the SVD (Singular Value Decomposition) compression. In particular, we divide the cover image into blocks and apply the SVD to each block; the watermark is embedded in all the non-zero singular values according to the local features of the cover image so as to balance embedding capacity with distortion. The watermarking system we propose is robust against typical attacks, including low-pass and high-pass filtering, as evaluated by the Checkmark benchmarking tool
The chapter illustrates watermarking based on the transform domain. It argues that transform-based watermarking is robust to possible attacks and imperceptible with respect to the quality of the multimedia file we would like to protect. Among those transforms commonly used in communications, we emphasize the use of singular value decomposition (SVD) for digital watermarking. The main advantage of this choice is flexibility of application. In fact, SVD may be applied in several fields where data are organized as matrices, including multimedia and communications. We present a robust SVD-based watermarking scheme for images. According to the detection steps, the watermark can be determined univocally, while other related works present flaws in watermark detection. A case study of our approach refers to the protection of geographical and spatial data in case of the raster representation model of maps.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.