Robust Watermarking and Affine Registration of 3D Meshes
IH '02 Revised Papers from the 5th International Workshop on Information Hiding
Neural Network Theory
An Intelligent Digital Right Management System Based on Multi-agent
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 01
The use of digital watermarking for intelligence multimedia document distribution
Journal of Theoretical and Applied Electronic Commerce Research
Three-dimensional meshes watermarking: review and attack-centric investigation
IH'07 Proceedings of the 9th international conference on Information hiding
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Watermarking based DRM implementations insert imperceptible information or watermark in digital media to trace owner of the content and deter the illegal distribution of media. In geometry based 3D watermarking algorithms, a watermark is inserted by modifying the coordinates of vertices in the mesh. It is a requirement of watermarking algorithms that this change in vertex coordinates shouldn't cause perceptible distortion. It has always been a challenge to select vertices in the 3D model which would not cause perceptible distortion on addition of watermark. This paper proposes a novel approach to overcome this challenge using Artificial Neural Networks (ANN). Feature vectors representing the geometry of the vertex and its surrounding vertices are extracted and used to train and simulate ANN. ANN is used as a classifier to determine which vertices should be selected for watermarking. Experimental results simulate various attacks to test the robustness of the algorithm.