Abstract
Image scramble is one of the key technologies in the digital watermarks. In the absence of standardization and specific requirements in Watermark procedures, there are many methods for image scramble. In order to improve robustness, secrecy and exclusion of scrambled image, a method of neural network image scramble for wavelet watermark is proposed in this paper. Because the nonlinear mapping from the original image to its scrambled image is the key for image scramble, the nonlinear feature of neural network can be used to get the scrambled image. Our method embeds watermark into the wavelet descriptors. Watermark scrambled image generated by neural network can be successfully detected even after rotation, translation, scaling. And watermarks of our scheme are good at defending many kind watermark attacks. The experimental results demonstrate that our watermark algorithm is useful and practical.
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© 2005 Springer-Verlag Berlin Heidelberg
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Zhao, J., Zhao, Q., Zhou, Mq., Pan, J. (2005). A Novel Wavelet Watermark Algorithm Based on Neural Network Image Scramble. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_51
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DOI: https://doi.org/10.1007/11539117_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28325-6
Online ISBN: 978-3-540-31858-3
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