A Blind Watermarking Scheme for Three-Dimensional Mesh Models Based on Statistical Characteristic of Vertices

To obtain a better balance between the robustness and transparency of the blind watermarking scheme for three-dimensional mesh models, a novel blind watermarking scheme based on statistical characteristic of vertices is proposed in this paper. In the embedding process, the distances from vertices to the model center are calculated as their eigenvalues based on which vertices are separated into bins that are further classified into three groups: united bins, recovery bins and buffer bins according to the distribution of eigenvalues. Watermark is embedded by adjusting the distribution of normalized eigenvalues in united bins and then the position of the model center is recovered through modifying the coordinates of vertices in recovery bins. The proposed scheme enhances the robustness owing to the comprehensive utilization of united bins, recovery bins and vertex fine-tuning method while achieves the blind detection of watermark. The experimental results show that the proposed scheme not only has a good performance in transparency but also can effectively resist the common attacks including translation, rotation, uniform scaling, vertex rearrangement, noise, smoothing, subdivision and remeshing.