Scale-invariant image watermarking via optimization algorithms for quantizing randomized statistics

Authors:
Tie Liu;Ramarathnam Venkatesan;M. Kivanç Mihçak
Affiliations:
University of Illinois, Urbana-Champaign, Urbana, IL;Microsoft Research, Redmond, WA;Microsoft Research, Redmond, WA
Venue:
Proceedings of the 2004 workshop on Multimedia and security
Year:
2004

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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].