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Improved Algorithms for Robust Histogram Shape-Based Image Watermarking

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Digital Forensics and Watermarking (IWDW 2017)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10431))

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Abstract

In histogram shape-based watermarking schemes, watermark bits are embedded by altering the shape of a histogram extracted from the host image. Exited embedding algorithms use a group of histogram bins to embed only one watermark bit, which results in a rather low watermark capacity. In this paper, we improve the embedding algorithm in two new ways. The first proposed algorithm performs multi-round embedding to carry more watermark bits. In each round of embedding, a specified histogram is extracted so that the embedding operation does not affect watermark bits embedded in previous rounds. The second proposed algorithm uses a group of histogram bins to embed more than one watermark bits, where the coefficient transferring is optimized to minimize the embedding distortion. These algorithms can effectively enlarge the capacity. Furthermore, a histogram preadjustment method, together with a refined coefficient transferring method, is introduced. As a result, reasonable performances on robustness and watermarked image quality are available. The proposed algorithms provide various tradeoff among capacity, robustness, and perceptibility, which supports a wide range of applications.

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Acknowledgements

This work was supported by National Science Foundation of China (Grant Nos. 61472165 and 61373158), Guangdong Provincial Engineering Technology Research Center on Network Security Detection and Defence (Grant No. 2014B090904067), Guangdong Provincial Special Funds for Applied Technology Research and development and Transformation of Important Scientific and Technological Achieve (Grant No. 2016B010124009), the Zhuhai Top Discipline–Information Security, Guangzhou Key Laboratory of Data Security and Privacy Preserving, Guangdong Key Laboratory of Data Security and Privacy Preserving.

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Authors and Affiliations

  1. College of Information Science and Technology, Jinan University, Guangzhou, 510632, China

    Bingwen Feng & Jian Weng

  2. School of Data and Computer Science, Guangdong Key Laboratory of Information Security Technology, Sun Yat-sen University, Guangzhou, 510006, China

    Wei Lu

Authors
  1. Bingwen Feng
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  2. Jian Weng
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  3. Wei Lu
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Corresponding author

Correspondence to Jian Weng .

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Editors and Affiliations

  1. Department of Computer Science, Otto-von-Guericke University Magdeburg, Magdeburg, Germany

    Christian Kraetzer

  2. Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA

    Yun-Qing Shi

  3. Department of Computer Science, Otto-von-Guericke University Magdeburg, Magdeburg, Germany

    Jana Dittmann

  4. Graduate School Information Security, Korea University, Seoul, Korea (Republic of)

    Hyoung Joong Kim

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Feng, B., Weng, J., Lu, W. (2017). Improved Algorithms for Robust Histogram Shape-Based Image Watermarking. In: Kraetzer, C., Shi, YQ., Dittmann, J., Kim, H. (eds) Digital Forensics and Watermarking. IWDW 2017. Lecture Notes in Computer Science(), vol 10431. Springer, Cham. https://doi.org/10.1007/978-3-319-64185-0_21

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  • DOI: https://doi.org/10.1007/978-3-319-64185-0_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64184-3

  • Online ISBN: 978-3-319-64185-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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