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一种基于八叉树的三维网格盲水印算法
引用本文:齐越,舒军,沈旭昆,蔡苏.一种基于八叉树的三维网格盲水印算法[J].北京航空航天大学学报,2008,34(3):331-335.
作者姓名:齐越  舒军  沈旭昆  蔡苏
作者单位:北京航空航天大学 虚拟现实技术与系统国家重点实验室, 北京 100083
基金项目:国家自然科学基金,教育部科学技术研究重大项目,科技部科技支撑计划,北京市科委资助项目
摘    要:鲁棒性数字水印特别是盲水印是保护数字作品版权的重要手段.提出一种针对三维网格模型的盲水印算法.首先通过PCA(Principle Component Analysis)对模型进行预处理,将模型调整到唯一的姿态朝向,然后对三维模型进行剖分得到八叉树.对有意义的RGB(Red, Green, Blue)水印信息图进行随即置乱生成密钥,并将水印信息量化并作为细微扰动信息嵌入到八叉树底层节点包含的顶点坐标中.提取水印时不需要原始模型数据,且与模型拓扑无关,可直接对点云数据进行水印嵌入.特点是嵌入容量大,可抵抗旋转、平移、均匀缩放和顶点重排序攻击.根据八叉树高层节点编码抽取模型的特征来构造零水印,并注册到第三方公证处,还可以在一定程度上抵抗均匀化简、噪声和重新网格化等攻击,具有较强的鲁棒性和普适性. 

关 键 词:三维    主成分分析    鲁棒性    水印
文章编号:1001-5965(2008)03-0331-05
收稿时间:2007-06-29
修稿时间:2007年6月29日

Octree-based blind watermarking on 3D meshes
Qi Yue,Shu Jun,Shen Xukun,Cai Su.Octree-based blind watermarking on 3D meshes[J].Journal of Beijing University of Aeronautics and Astronautics,2008,34(3):331-335.
Authors:Qi Yue  Shu Jun  Shen Xukun  Cai Su
Institution:State Key Laboratory of Virtual Reality Technology and System, Beijing University of Aeronantics And Astronautics, Beijing 100083, China
Abstract:Robust blind watermarking is the important method for digital works copyright protection.A novel blind watermarking method on 3D meshes was proposed.PCA(primary component analysis) was used for 3D meshes' preprocessing to make a unique model posture.After making division of the 3D meshes based octree,octree structure could be obtained.A random scrambling was made for the RGB(red,green,blue) meaningful watermark image before embedding it into the bottom octree nodes.This method can be used directly on points-cloud,as it does nothing with the topology of the meshes.It is robust against translation,rotation,uniform scaling and random vertex reordering attacks.In addition,a method to generate 'Zero-Watermark' based on higher codec of octree nodes was given.The 'Zero-watermark' was then registered in the third-party of notarization,and it can be robust against simplification,noise addition and remeshing attacks in some extent.This method has a big volume for embedding and high popularity.
Keywords:three dimensional  principal component analysis  robustness  watermarking
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