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

journal contribution
posted on 03.05.2022, 14:25 by Xiyao Liu, Yayun Zhang, Jiayu Wang, Yuying Sun, Wei Zhang, Di Zhou, Gerald SchaeferGerald Schaefer, Hui FangHui Fang

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 suffcient 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.

Funding

National Natural Science Foundations of China (61602527, 61772555, 61772553, U1734208)

Natural Science Foundation of Hunan Province, China (2020JJ4746).

History

School

  • Science

Department

  • Computer Science

Published in

Information Sciences

Publisher

Elsevier

Version

AM (Accepted Manuscript)

Publisher statement

This paper was accepted for publication in the journal Information Sciences and the definitive published version is available at [insert DOI link].

Acceptance date

02/05/2022

ISSN

0020-0255

Language

en

Depositor

Dr Hui Fang. Deposit date: 2 May 2022