数字媒体取证与安全

网格谱系数下不可见性指导的鲁棒水印算法

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  • 1. 太原理工大学 计算机科学与技术学院(大数据学院), 山西 晋中 030600;
    2. 北京邮电大学 人工智能学院, 北京 100876;
    3. 中国科学院自动化研究所, 北京 100190

收稿日期: 2024-11-12

  网络出版日期: 2025-06-23

基金资助

国家重点研发计划青年科学家项目(No.2021YFF0900100);中央高校基本科研业务费专项资金项目(No.2024RC12);山西省重点研发计划项目(No.202102010101004)

Robust Watermarking Algorithm Guided by Invisibility Under Mesh Spectral Coefficients

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  • 1. College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Jinzhong 030600, Shanxi, China;
    2. College of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    3. Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

Received date: 2024-11-12

  Online published: 2025-06-23

摘要

在版权保护领域,网格水印技术是保护3D模型在传输过程中免受恶意攻击的关键技术,然而现有的网格水印算法并未充分联系空域和频域,对水印嵌入强度的设置规则不够清晰。针对此问题,本文提出了一种受不可见性指导的鲁棒水印算法(robust watermarkingalgorithm guided by invisibility,RWGI)。以三维网格的拉普拉斯变换为对象,在水印嵌入过程中对空域不可见性评价指标与频谱域嵌入强度的关系进行建模,使水印的嵌入受到不可见性指标的调控,保证了水印嵌入强度的按需量化;针对该指导的实施过程,设计了一种基于绝对值的谱系数寻优策略和一种简单高效的网格分块算法。实验表明,本文提出的算法具有良好的不可见性和对常见攻击的鲁棒性,且能保证水印嵌入强度对模型尺度的自适应。

本文引用格式

吴肖, 黄樱, 宋春花, 关虎, 牛保宁 . 网格谱系数下不可见性指导的鲁棒水印算法[J]. 应用科学学报, 2025 , 43(3) : 370 -386 . DOI: 10.3969/j.issn.0255-8297.2025.03.002

Abstract

In the field of copyright protection, mesh watermarking is a key technology for protecting 3D models from malicious attacks during transmission. However, existing watermarking algorithms for 3D meshes often fail to effectively connect the spatial and frequency domains and the setting rule of watermark embedding strength is not clear enough. To solve this problem, we propose a robust mesh watermarking algorithm guided by invisibility (RWGI). Taking the Laplacian transform of a mesh as an example, we establish, for the first time during the watermark embedding process, a model that characterizes the relationship between the spatial-domain invisibility evaluation index and the spectraldomain embedding strength. In this way, the watermark embedding can be adaptively guided by the invisibility index, ensuring the quantification of the watermark embedding strength on demand. Additionally, we design a spectral coefficient optimization strategy based on absolute value, along with a simple yet efficient watermarking segmentation algorithm. Experimental results show that the proposed algorithm achieves strong invisibility, robustness against common attacks, and adaptive control of watermark embedding intensity with respect to model scale.

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