Octree-based Robust Watermarking for 3D Model

Abstract

Three robust blind watermarking methods of 3D models based on Octree are proposed in this paper: OTC-W, OTP-W and Zero-W. Primary Component Analysis and Octree partition are used on 3D meshes. A scrambled binary image for OTC-W and a scrambled RGB image for OTP-W are separately embedded adaptively into the single child nodes at the bottom level of Octree structure. The watermark can be extracted without the original image and 3D model. Those two methods have high embedding capacity for 3D meshes. Meanwhile, they are robust against geometric transformation (like translation, rotation, uniform scaling) and vertex reordering attacks. For Zero-W, higher nodes of Octree are used to construct ‘Zero-watermark’, which can resist simplification, noise and remeshing attacks. All those three methods are fit for 3D point cloud data and arbitrary 3D meshes. Three robust blind watermarking methods of 3D models based on Octree are proposed in this paper: OTC-W, OTP-W and Zero-W. Primary Component Analysis and Octree partition are used on 3D meshes. A scrambled binary image for OTC-W and a scrambled RGB image for OTP-W are separately embedded adaptively into the single child nodes at the bottom level of Octree structure. The watermark can be extracted without the original image and 3D model. Those two methods have high embedding capacity for 3D meshes. Meanwhile, they are robust against geometric transformation (like translation, rotation, uniform scaling) and vertex reordering attacks. For Zero-W, higher nodes of Octree are used to construct ‘Zero-watermark’, which can resist simplification, noise and remeshing attacks. All those three methods are fit for 3D point cloud data and arbitrary 3D meshes.