Tie Liu
ABSTRACT
We introduce a novel approach for blind and semi-blind watermarking and apply it to images. We derive randomized robust semi-global features of images in a suitable transform domain (wavelets in case of images) and quantize them in order to embed the watermark. Quantization is carried out by embedding to the host a computed sequence via solving an optimization problem whose parameters are known to the information hider, but unknown to the attacker. The image features are rationa statistics of pseudo-random regions; these statistics are by construction invariant against scaling attacks and approximately invariant against several contrast enhancement modifications (such as histogram equalization). This scheme can be seen as an improved version of our previous image watermarking algorithm [1].
- M. K. Mihçak, R. Venkatesan, and M. Kesal, "Watermarking via optimization algorithms for quantizing randomized statistics of image regions," in Proc. 40th Annual Allerton Conf. on Communication, Control and Computing Monticello, Illinois, October 2002.]]Google Scholar
- F. Petitcolas, R. Anderson, and M. Kuhn. "Attacks on copyright marking systems," in Proc. 2nd Int. Workshop on Information Hiding Port and, Oregon, April 1998.]] Google ScholarDigital Library
- R. Venkatesan, S. Koon, M. Jakubowski, and P. Moulin, "Robust Image Hashing," in Proc. Int. Conf. Image Processing Vancouver, Canada, September 2000.]]Google Scholar
- T. Liu and P. Moulin, "Error exponents for one-bit watermarking," in Proc. Int. Conf. Acoustics, Speech, and Signal Processing Hong Kong, April 2003.]]Google Scholar
- M. K. Mihçak and P. Moulin, "Information embedding codes matched to ocally stationary Guassian image models," in Proc. Int. Conf. Image Processing Rochester, New York, September 2002.]]Google ScholarCross Ref
Index Terms
- Scale-invariant image watermarking via optimization algorithms for quantizing randomized statistics
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