Optimal watermark detection based on support vector machines

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Abstract

In this paper, a novel optimal watermark detection scheme based on support vector machine and error correcting codes is proposed. To extract the watermark bits from a possibly corrupted marked image with a lower error probability, we apply both the good generalization ability of support vector machine and the error correction code BCH. Due to the good learning ability of support vector machine, it can learn the relationship between the embedded information and corresponding watermarked image; when the watermarked image is attacked by some intentional or unintentional attacks, the trained support vector machine can recover the right hidden information bits. © Springer-Verlag 2004.

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Fu, Y., Shen, R., & Lu, H. (2004). Optimal watermark detection based on support vector machines. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3173, 552–557. https://doi.org/10.1007/978-3-540-28647-9_91

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