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Robustness Enhancement of Content-Based Watermarks Using Entropy Masking Effect

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Digital Watermarking (IWDW 2005)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 3710))

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Abstract

Image-Adaptive watermarking systems exploit visual models to adapt the watermark to local properties of the host image. This leads to a watermark power enhancement, hence an improved resilience against different attacks, while keeping the mark imperceptible. Visual models consider different properties of the human visual system, such as frequency sensitivity, luminance sensitivity and contrast masking. Entropy masking is another human visual system’s characteristic, which rarely has been addressed in visual models. In this paper we have utilized this masking effect to improve the robustness of Image-Adaptive watermarks while keeping their transparency. Experimental results show a significant amount of enhancement to the power of watermark. The work has been expanded to video watermarking, considering special properties of the entropy masking effect.

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Author information

Authors and Affiliations

  1. Electrical Engineering Department, Sharif University of Technology, Azadi st., Tehran, Iran

    Amir Houman Sadr

  2. Electronic Research Center, Sharif University of Technology, Azadi st., Tehran, Iran

    Shahrokh Ghaemmaghami

Authors
  1. Amir Houman Sadr
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  2. Shahrokh Ghaemmaghami
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Editor information

Editors and Affiliations

  1. Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Siena, Italy

    Mauro Barni

  2. University College London, Torrington Place, UK

    Ingemar Cox

  3. Hewlett-Packard Laboratories, Palo Alto, CA, USA

    Ton Kalker

  4. Multimedia Security Lab, Korea University, Science Campus, 136-701, Seoul, Korea

    Hyoung-Joong Kim

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© 2005 Springer-Verlag Berlin Heidelberg

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Sadr, A.H., Ghaemmaghami, S. (2005). Robustness Enhancement of Content-Based Watermarks Using Entropy Masking Effect. In: Barni, M., Cox, I., Kalker, T., Kim, HJ. (eds) Digital Watermarking. IWDW 2005. Lecture Notes in Computer Science, vol 3710. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11551492_34

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  • DOI: https://doi.org/10.1007/11551492_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28768-1

  • Online ISBN: 978-3-540-32052-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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