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An Information Hiding Algorithm of 3D Model Based on Curvature Radius

Published: 05 February 2024 Publication History

Abstract

The main focus of current information hidding algorithms is to improve the robustness and capacity of the algorithms but there are still certain drawbacks in invisibility. Therefore, an information hiding algorithm based on curvature radius of 3D models is proposed. The first step is to calculate the curvature of every triangle in each 3D model. Then, use a clustering algorithm to group the triangles based on their curvature radius. The second step is to calculate their mean curvature radius. Then, by changing the mean curvature of each group, embed the transformed and optimized secret information. Finally, the vertices of the chosen triangular patch are modified to lessen the influence of the secret information on the 3D model, thereby reducing the distortion of the marked model. The experimental results reveal that, in comparison with VLR and MPS algorithms, the algorithm has increased the mean SNR values by 4.31% and 8.57% respectively and improved invisibility. For robustness, the algorithm’s Corr value increased by 1.13% and 25.53%; 7.54 and 17.67%; 5.19% and 25.68%; 6.08% and 15.11%, when faced with 2% noise attack, 60% mesh simplification, 30% cutting, and 60% compression.

References

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Ashish Girdhar and Vijay Kumar. 2019. A reversible and affine invariant 3D data hiding technique based on difference shifting and logistic map. Journal of Ambient Intelligence and Humanized Computing (2019).
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Jing Liu, Yinghui Wang, Ye Li, Ruijiao Liu, and Jinlei Chen. 2017. A robust and blind 3D watermarking algorithm using multiresolution adaptive parameterization of surface. Neurocomputing 237, 24 (2017), 304–315.
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Wanli Lv, Lulu Cheng, and Zhaoxia Yin. 2021. High Capacity Reversible Data Hiding in Encrypted 3D mesh models Based on multi-MSB Prediction. (2021).
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Nassima Medimegh, Samir Belaid, Mohamed Atri, and Naoufel Werghi. 2018. 3D mesh watermarking using salient points. Multimedia Tools and Applications 77, 24 (2018), 32287–32309.
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Fei Peng, Tongxin Liao, and Min Long. 2022. A Semi-Fragile Reversible Watermarking for Authenticating 3D Models in Dual Domains Based on Variable Direction Double Modulation. IEEE Transactions on Circuits and Systems for Video Technology 32, 12 (2022), 8394–8408. https://doi.org/10.1109/TCSVT.2022.319254
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Zillur Rahman, Md. Sabir Hossain, Mohd. Hasan, and Ahmed Imteaj. 2021. An enhanced method of initial cluster center selection for K-means algorithm. 2021 Innovations in Intelligent Systems and Applications Conference (ASYU) 77, 24 (2021), 1–6. https://api.semanticscholar.org/CorpusID:244406669
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Guoyou W. J. Zhang and J. Li. 2022. Zero-watermarking algorithm for three-dimensional mesh model based on vector length ratio. Computer Systems and Applications 31, 7 (2022), 165–171.

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  1. An Information Hiding Algorithm of 3D Model Based on Curvature Radius

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    CECCT '23: Proceedings of the 2023 International Conference on Electronics, Computers and Communication Technology
    November 2023
    266 pages
    ISBN:9798400716300
    DOI:10.1145/3637494
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 05 February 2024

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    Author Tags

    1. 3D models
    2. clustering algorithm
    3. curvature radius
    4. information hiding
    5. invisibility

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    • Research-article
    • Research
    • Refereed limited

    Funding Sources

    • the Fundamental Research Funds for the Central Universities, CHD
    • the National Natural Science Foundation of China

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    CECCT 2023

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