Robust Image Watermarking Based on Local Zernike Moments

Invariant image features can be used to carry watermarks so as to improve the robustness of the watermarks against geometric transformations. However, most previous watermarking algorithms using invariant features are still sensitive to cropping attacks and combinations of rotation, scaling, and translation (RST) attacks. To improve the resilience against these attacks, we propose a multi-bit image watermarking algorithm using local Zernike moments (LZMs). The magnitude of LZMs are dither-modulated to embed watermark bits. To achieve scale invariance, we restore the original sampling rate using invariant centroid and geometric moments. Simulation results demonstrate that the proposed watermarking algorithm is robust against various geometric attacks as well as signal processing attacks.