Multiple-feature-based zero-watermarking for robust and discriminative copyright protection of DIBR 3D videos

Abstract

Zero-watermarking is a key technique for achieving lossless and flexible copyright protection of depth image-based rendering (DIBR) videos. Existing approaches extract features of both 2D frames and depth maps via a single mechanism to protect them simultaneously. However, it is difficult for these schemes to fully satisfy the copyright protection requirements of the two components, including the remarkable discriminative capability of 3D videos and robustness against various attacks. Hence, in this paper, we propose a novel multiple-feature-based zero-watermarking scheme to protect the copyright of DIBR 3D videos. To the best of our knowledge, this is the first scheme that integrates multiple features to improve both the discriminative capability and robustness against various attacks. Specifically, dual-tree complex wavelet transform and discrete cosine transform features enhance the robustness against DIBR conversion and noise addition, respectively, while ring-partition statistical residual features ensure robustness against geometric attacks and provide sufficient discriminative capacity. In addition, we use a logistic-logistic chaotic system to encrypt these multiple features for enhanced security and design an attention-based fusion approach to offer an optimal copyright protection solution. Extensive experimental results demonstrate that our proposed scheme has stronger robustness and discriminative capacity compared to state-of-the-art zero-watermarking methods.