Dong Zheng
Abdulmotaleb El Saddik
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Abstract
In this article, we review the algorithms for rotation, scaling and translation (RST) invariant image watermarking. There are mainly two categories of RST invariant image watermarking algorithms. One is to rectify the RST transformed image before conducting watermark detection. Another is to embed and detect watermark in an RST invariant or semi-invariant domain. In order to help readers understand, we first introduce the fundamental theories and techniques used in the existing RST invariant image watermarking algorithms. Then, we discuss in detail the work principles, embedding process, and detection process of the typical RST invariant image watermarking algorithms. Finally, we analyze and evaluate these typical algorithms through implementation, and point out their advantages and disadvantages.
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Index Terms
- A survey of RST invariant image watermarking algorithms
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Reviews
Suya You
Existing digital watermarking techniques are systematically reviewed in this paper, with a special focus on rotation, scaling, and translation (RST) invariant image watermarking algorithms. The RST invariant-based approach has recently demonstrated its effectiveness in performance and robustness against various geometrical transformations and image degradations. The paper comprehensively covers existing algorithms and provides a detailed performance analysis. The authors did a good job in structuring and organizing the content, which made the paper very readable. My only concern is with Section 2, “Fundamental Theories and Techniques,” which seems too long (17 pages). It basically reviews very fundamental image processing knowledge that could be easily found in any image processing textbook; I assume that readers interested in this paper already have such knowledge. Also, it would have been nice if the authors had included a section at the end to comment on future work and possible research directions in this area (according to their findings and experiences in this domain). Overall, this is a very good and comprehensive survey paper—I highly recommend it. Online Computing Reviews Service
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