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基于顶点划分和坐标标准化的密文域 3 维网格模型可逆信息隐藏

  • Wanli Lü
  • , Yun Tang
  • , Zhaoxia Yin*
  • , Bin Luo
  • *此作品的通讯作者
  • Anhui University

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

Reversible data hiding in encrypted domain enables the secure and confidential embedding of additional information in encrypted multimedia, ensuring the privacy and integrity of both the carrier and the embedded data during transmission. The authorized recipients can extract the data without any loss and recover the media successfully. In the realm of digital media, 3D mesh models, being a relatively nascent form, possesses a distinctive file structure markedly different from that of conventional image media. Consequently, limited research has been conducted in this domain. Augmenting the embedding capacity of 3D mesh models in the encrypted domain poses an enduring challenge. The direct application of multiple most significant bit prediction algorithm from the image domain to 3D mesh models is impeded by disparities in data storage formats, thus encumbering the predictive performance of algorithms. To effectively tackle this issue, we propose the adoption of coordinate standardization to eliminate the influence of the sign bit and ameliorate the prediction algorithm’s overall performance. In order to further mitigate the inclusion of redundant auxiliary information, we introduce the integration of the selection of embedding set vertices into our experiments, which effectively generates additional payload space. The experimental results affirm that our purposed methodology attains the maximum embedding capacity while guaranteeing lossless and separable recovery of both the model and the embedded information, surpassing the capabilities of existing techniques.

投稿的翻译标题Reversible Data Hiding for 3D Mesh Model in Encrypted Domain Based on Vertex Partition and Coordinate Standardization
源语言繁体中文
页(从-至)1536-1544
页数9
期刊Jisuanji Yanjiu yu Fazhan/Computer Research and Development
卷61
期6
DOI
出版状态已出版 - 2024

关键词

  • 3D mesh model
  • embedding capacity
  • encrypted domain
  • prediction error
  • reversible data hiding

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