Desynchronization attacks resilient image watermarking scheme based on global restoration and local embedding

For the existing feature-based image watermarking schemes, it is still a challenge to resist against desynchronization attacks. In this paper, we propose a new feature-based image watermarking scheme for improving the robustness against desynchronization attacks. First, multi-scale Gaussian filtering model is used to extract feature points in original image. The stable and non-overlapped local circular regions centered at feature points are thereafter selected by combining image segmentation and feature points refinement. Finally the watermark is embedded in the Zernike moments of the normalized circular regions. In watermark detection, a suspected image is restored with the geometrical transform matrix which is calculated by feature points matching and RANSAC iteration algorithm. The watermark detection is then conducted in the normalized circular regions after the same feature selection procedure as the embedding one. Preliminary experiments show that the proposed image watermarking can be robust against various attacks including common image processing attacks and desynchronization attacks, even complicated attacks.