Affine invariant image watermarking using intensity probability density-based Harris Laplace detector
Feature point based image watermarking against geometric distortions has attracted great attention in recent years. However, for the state-of-the-art intensity based feature points detectors, the feature points often gather at textured portions of the image or on the edges where the change of intensity is significant, so that many feature points capture the same portion of the image, which makes the watermark be vulnerable to local geometric distortions. In this paper, we propose an affine invariant image watermarking scheme with good visual quality and reasonable resistance toward local geometric distortions, which utilizes the intensity probability density-based HarrisLaplace detector. Firstly, the uniform and robust feature points are extracted by utilizing modified HarrisLaplace detector, in which the intensity probability density gradient is used instead of intensity gradient. Then, the affine invariant local ellipse regions (LERs) are constructed adaptively according to the variation of local intensity probability density. Finally, the digital watermark is embedded into the affine invariant LERs in nonsubsampled contourlet transform (NSCT) domain by modulating the lowpass NSCT coefficients. By binding the watermark with the affine invariant LERs, the watermark detection can be done without synchronization error. Experimental results show that the proposed image watermarking is not only invisible and robust against common image processing operations such as sharpening, noise adding, and JPEG compression, but also robust against the global affine transforms and local geometric distortions.
image watermarking geometric distortion harrislaplace detector intensity probability density affine invariant local ellipse region nonsubsampled contourlet transform synchronization error image feature point