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Volume 45 Issue 12
Dec.  2019
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Journal of Beijing University of Aeronautics and Astronautics  > 2019  >  45(12): 2403-2414.
Liu Shenquan, Lu Qishao, Wang Qiet al. Traveling Waves of the Cahn-Hilliard Equation[J]. Journal of Beijing University of Aeronautics and Astronautics, 1998, 24(5): 584-587. (in Chinese)
Citation: HUANG Ying, NIU Baoning, GUAN Hu, et al. Image texture based adaptive watermarking algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(12): 2403-2414. doi: 10.13700/j.bh.1001-5965.2019.0369(in Chinese)
shu

Image texture based adaptive watermarking algorithm

doi: 10.13700/j.bh.1001-5965.2019.0369
  • 1.

    College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China

  • 2.

    Digital Content Technology and Media Service Research Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

Funds:

National Key R & D Program of China 2017YFB1401000

International Cooperation Project of the Major R & D Program of Shanxi 201603D421015

More Information
  • Corresponding author: NIU Baoning, E-mail: niubaoning@tyut.edu.cn
  • Received Date: 09 Jul 2019
  • Accepted Date: 20 Aug 2019
  • Publish Date: 20 Dec 2019
    Abstract

  • Watermarking is a technique of embedding a mark called a watermark in an image to prove the copyright of this image. This paper proposes an image texture based adaptive watermarking algorithm by taking advantage of the textured regions of an image being easy to hide the watermark. Firstly, a texture measurement method is proposed to reflect the richness of image's texture, and the concepts of global texture value and local texture value are introduced to comprehensively analyze the image texture distribution. The textured regions of an image are located by using the sliding window and judged by the local texture value of the inner window area, and then we only embed the watermark in the textured regions and ensure the visual quality of embedded watermark. The function relationship among the global texture value, the local texture value of the textured regions and the embedding parameter is obtained by multiple regression analysis. It can adaptively adjust the embedding parameters with the texture values of the regions to maximally enhance the imperceptibility and robustness of the watermark. Moreover, embedding the same watermark in multiple non-overlapping textured regions further improves the accuracy of the extracted watermark. The simulation experiments on 100 images show the superiority of the proposed method compared with the state-of-the-art methods in terms of imperceptibility, adaptivity and robustness.

     

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    • References(23)
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