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Color Image Watermarking Algorithm Using BPN Neural Networks

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Neural Information Processing (ICONIP 2006)

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

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Abstract

This paper proposes a new watermarking scheme in which a logo watermark is embedded into the discrete wavelet transform (DWT) domain of the color image using Back-Propagation Neural networks (BPN). In order to strengthen the imperceptibility and robustness, the original image is transformed from RGB color space to brightness and chroma space (YCrCb). After transformation, the watermark is embedded into DWT coefficient of chroma component, CrCb. A secret key determines the locations in the image where the watermark is embedded. This process prevents possible pirates from removing the watermark easily. BPN will learn the characteristics of the color image, and then watermark is embedded and extracted by using the trained neural network. Experimental results show that the proposed method has good imperceptibility and high robustness to common image processing attacks.

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© 2006 Springer-Verlag Berlin Heidelberg

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Piao, CR., Cho, S., Han, SS. (2006). Color Image Watermarking Algorithm Using BPN 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_27

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  • DOI: https://doi.org/10.1007/11893295_27

  • 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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