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High Capacity Reversible Data Hiding for Encrypted 3D Mesh Models Based on Topology

  • Yun Tang
  • , Lulu Cheng
  • , Wanli Lyu
  • , Zhaoxia Yin*
  • *此作品的通讯作者
  • Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Anhui University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

Reversible data hiding in encrypted domain(RDH-ED) can not only protect the privacy of 3D mesh models and embed additional data, but also recover original models and extract additional data losslessly. However, due to the insufficient use of model topology, the existing methods have not achieved satisfactory results in terms of embedding capacity. To further improve the capacity, a RDH-ED method is proposed based on the topology of the 3D mesh models, which divides the vertices into two parts: embedding set and prediction set. And after integer mapping, the embedding ability of the embedding set is calculated by the prediction set. It is then passed to the data hider for embedding additional data. Finally, the additional data and the original models can be extracted and recovered respectively by the receiver with the correct keys. Experiments declare that compared with the existing methods, this method can obtain the highest embedding capacity.

源语言英语
主期刊名Digital Forensics and Watermarking - 21st International Workshop, IWDW 2022, Revised Selected Papers
编辑Xianfeng Zhao, Zhenjun Tang, Pedro Comesaña-Alfaro, Alessandro Piva
出版商Springer Science and Business Media Deutschland GmbH
页205-218
页数14
ISBN(印刷版)9783031251146
DOI
出版状态已出版 - 2023
活动21st International Workshop on Digital-Forensics and Watermarking, IWDW 2022 - Guilin, 中国
期限: 18 11月 2022 → 19 11月 2022

丛书

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷13825 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议21st International Workshop on Digital-Forensics and Watermarking, IWDW 2022
国家/地区中国
市Guilin
时期18/11/22 → 19/11/22

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