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International Conference on Future Generation Communication and Networking

FGCN 2009: Communication and Networking pp 586–593Cite as

Enhanced SVD Based Watermarking with Genetic Algorithm

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 56))

Abstract

In this paper, we propose an enhanced robust watermarking algorithm based on singular vector decomposition(SVD). Previous SVD based watermarking algorithms have a problem of false-positive detection. For solving this problem, our algorithm performs an extra verification job for watermark using reference images. To find optimal scaling factors in the algorithm which satisfy both robustness and high quality of the watermarked image, we employed the genetic algorithm(GA).

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References

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Author information

Authors and Affiliations

  1. Gwangju Institute of Science and Technology, Gwangju, 500-712, Korea

    Heechul Jung & Moongu Jeon

Authors
  1. Heechul Jung
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  2. Moongu Jeon
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Editor information

Editors and Affiliations

  1. University of Warsaw & Infobright Inc., Poland

    Dominik Ślęzak

  2. Hannam University, 306-791, Daejeon, South Korea

    Tai-hoon Kim

  3. National Chung Cheng University, Chiayi County, Taiwan

    Alan Chin-Chen Chang

  4. University of Western Macedonia, West Macedonia, Greece

    Thanos Vasilakos

  5. Tianjin University, China

    MingChu Li

  6. Faculty of Information Science and Electrical Engineering, Kyushu University, 6-10-1 Hakozaki, 812-8581, Fukuoka, Japan

    Kouichi Sakurai

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© 2009 Springer-Verlag Berlin Heidelberg

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Cite this paper

Jung, H., Jeon, M. (2009). Enhanced SVD Based Watermarking with Genetic Algorithm. In: Ślęzak, D., Kim, Th., Chang, A.CC., Vasilakos, T., Li, M., Sakurai, K. (eds) Communication and Networking. FGCN 2009. Communications in Computer and Information Science, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10844-0_69

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  • DOI: https://doi.org/10.1007/978-3-642-10844-0_69

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10843-3

  • Online ISBN: 978-3-642-10844-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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