A novel color image watermarking method based on genetic algorithm and neural networks

  • Authors:

  • Jialing Han;Jun Kong;Yinghua Lu;Yulong Yang;Gang Hou

  • Affiliations:

  • Computer School, Northeast Normal University, Changchun, Jilin Province, China and Key Laboratory for Applied Statistics of MOE, China;Computer School, Northeast Normal University, Changchun, Jilin Province, China and Key Laboratory for Applied Statistics of MOE, China;Computer School, Northeast Normal University, Changchun, Jilin Province, China;Computer School, Northeast Normal University, Changchun, Jilin Province, China;Computer School, Northeast Normal University, Changchun, Jilin Province, China and College of Humanities and Science, Northeast Normal University, Changchun, China

  • Venue:
  • ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
  • Year:
  • 2006

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Abstract

In the past a few years, many watermarking approaches have been proposed for solving the copyright protection problems, most of the watermarking schemes employ gray-level images to embed the watermarks, whereas the application to color images is scarce and usually works on the luminous or individual color channel. In this paper, a novel intensity adaptive color image watermarking algorithm based on genetic algorithm (CIWGA) is presented. The adaptive embedding scheme in color image's three component sub-images' wavelet coefficients, which belong to texture-active regions, not only improves image quality, but also furthest enhances security and robustness of the watermarked image. Then a novel watermark recovering method is proposed based on neural networks, which enhance the performance of watermark system successfully. The experimental results show that our method is more flexible than traditional methods and successfully fulfills the compromise between robustness and image quality.