Improved autocorrelation function based watermarking with side information

Abstract

We propose an improved autocorrelation function (ACF)based image watermarking that is robust to combined geometric and removal attacks. ACF-based watermarking is thought of as one of the most effective watermarking schemes that resist geometric attacks. In this watermarking scheme, the autocorrelation peaks of the watermark play an important role for geometric attack estimation. The peaks, however, are vulnerable to attacks. The proposed scheme enhances the performance of ACF-based watermarking by improving the strength of the peaks. The information of an original image is used at the embedding time, so that the detector can extract strong autocorrelation peaks. Experimental results show that the proposed scheme yields better robustness than conventional ACF based watermarking against combined geometric-removal attacks. 2005 SPIE and IS&T.