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Robust Multiple Watermarking Using Entropy Based Spread Spectrum

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Contemporary Computing (IC3 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 94))

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Abstract

Nowadays; information hiding has become a significant topic of computer science due to the increasing popularity of the Internet and the essential need of data security. With respect to the general information hiding problem, a tradeoff is involved between robustness, visibility and capacity. There are many watermarking techniques and models and each of them has some advantages and disadvantages. Mostly used in conjunction with spread spectrum watermarking, perceptual shaping refers to the idea of adjusting the strength of the watermark based on the perceptual sensitivity of a region in the image. All these methods use some model that assigns weights to various regions of the image. This weight determines the strength of the watermark that is added to that part of the image. This paper offers a way of embedding watermarks in a manner that increases robustness and reduces perceptual degradation and computational complexity. After an image is segmented, the entropy is calculated for each segment and only those segments that have entropy above some thresholds are considered for watermarking. This reduces the number of segments that are watermarked thereby economizing on computation and perceptual degradation. The choice of high entropy segments ensures that the method is robust, as low entropy segments would be more sensitive to attacks.

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Kamble, S., Maheshkar, V., Agarwal, S., Shrivastava, V. (2010). Robust Multiple Watermarking Using Entropy Based Spread Spectrum. In: Ranka, S., et al. Contemporary Computing. IC3 2010. Communications in Computer and Information Science, vol 94. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14834-7_47

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  • DOI: https://doi.org/10.1007/978-3-642-14834-7_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14833-0

  • Online ISBN: 978-3-642-14834-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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