A unified framework for robust 3D watermarking based on feature integration

In this paper, we present a unified framework for robust 3D embedded watermarking and non-embedded watermarking based on feature integration. It begins by segmenting a 3D model into multiple separate sub-models via empirical mode decomposition (EMD). And then, it constructs a robust feature image for each sub-model by integrating its explicit and implicit radial features. Such scheme enables our framework to seamlessly transition from 3D non-embedded watermarking to 3D embedded watermarking. Our 3D embedded watermarking modifies the model according to its statistical characteristics. Therefore, it is an adaptive embedding method and can improve the invisibility of 3D embedded watermarking. Subsequently, it generates the copyright-watermark keys by using an XOR operation on each feature image and the given watermark image. Additionally, our watermarking framework can extract multiple watermark images according to the feature images of the detected 3D model and the stored copyright-watermark keys. They can be combined into the final watermark via a voting strategy to enhance the robustness of 3D watermarking. The experimental results and analysis demonstrate the superior performance of our newly-proposed 3D watermarking framework in terms of versatility, robustness and invisibility.