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A Novel Color Image Watermarking Method Based on Genetic Algorithm and Neural Networks

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4234))

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.

This work is supported by science foundation for young teachers of Northeast Normal University, No. 20061002, China.

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© 2006 Springer-Verlag Berlin Heidelberg

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Han, J., Kong, J., Lu, Y., Yang, Y., Hou, G. (2006). A Novel Color Image Watermarking Method Based on Genetic Algorithm and Neural Networks. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893295_26

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  • DOI: https://doi.org/10.1007/11893295_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46484-6

  • Online ISBN: 978-3-540-46485-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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