Invariant image watermarking using multi-scale Harris detector and wavelet moments

Desynchronization attack is known as one of the most difficult attacks to resist, which can desynchronize the location of the watermark and hence causes incorrect watermark detection. It is a challenging work to design a robust image watermarking scheme against desynchronization attacks. Based on multi-scale Harris detector and wavelet moment theory, we propose a new content based image watermarking algorithm with low computational complexity, good visual quality and reasonable resistance toward desynchronization attacks in this paper. Firstly, the steady image feature points are extracted from the origin host by using multi-scale Harris detector, and the local feature regions (LFRs) are constructed adaptively according to the feature scale theory. Then, the LFRs are image normalized, and significant regions are obtained from the normalized LFRs by utilizing the invariant centroid theory. Finally, the digital watermark is embedded into the LFRs by modifying wavelet moment invariants of the significant regions. By binding the watermark with the geometrically invariant image features, 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 as sharpening, noise adding, and JPEG compression etc, but also robust against the desynchronization attacks such as rotation, translation, scaling, row or column removal, cropping, and local random bend etc.