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- W3037547418 abstract "When hiding information in a host image, different types of image features can be used as secret key. The cryptanalytic watermarking approach is recognized as robustness improvement solution for authentication stems and anti-forgery from attack. This work contributes a novel learning technique using saliency features of sub regions to establish a secret key and then apply the key like a parameter for both watermark embedding and watermark extracting. However, there is modification of the image features through insertion of information in watermark embedding. We propose to use learning methods together with saliency models, for assuring robustness of watermark extracting. Here, the image watermarking method is described with SVM learning and assistance of a number of saliency models. Our results show that the cryptanalytic watermarking method is sufficient to achieve invisibility and stability of watermark. Experimental results on a benchmark indicate the advantage of the saliency feature based method for anti-forgery applications." @default.
- W3037547418 created "2020-07-02" @default.
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- W3037547418 date "2020-06-30" @default.
- W3037547418 modified "2023-10-16" @default.
- W3037547418 title "Saliency Guided Image Watermarking for Anti-forgery" @default.
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- W3037547418 doi "https://doi.org/10.1007/978-3-030-49536-7_16" @default.
- W3037547418 hasPublicationYear "2020" @default.
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