Abstract
In this paper, we propose a robust and blind watermarking algorithm for 3D mesh models. Firstly, we extract salient feature points using a robust salient point detector based on Auto Diffusion Function (ADF). Afterwards, the mesh is segmented into different regions according to the detected salient points. Finally, we embed the watermark statistically into each region. During watermark embedding, the vertex norms are decomposed into normalized bins. Then, the watermark is embedded by modifying the amplitude depending on the watermark bit and the mean of each bin. In the extraction process, we extract the signature from each re-segmented region. Experiments conducted with a variety of mesh models evidenced the competitive performance of our watermarking scheme, in terms of the robustness and invisibility, when compared to other state of the art methods.