一种基于模糊c均值聚类的鲁棒三维网格水印算法

Ola M. El Zein , Lamiaa M. El Bakrawy , Neveen I. Ghali
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引用次数: 19

摘要

提出了一种基于模糊c均值聚类技术的鲁棒三维水印算法。FCM将三维网格的顶点聚类成合适和不合适的位置来插入水印,而不会产生明显的变形,而且攻击者很难确定水印的插入位置。提出了两种将水印插入三维网格模型的方法。第一种方法利用局部统计测量,如平均值和标准差,以改变顶点值的秘密水印数据到三维网格模型中,然而,第二种方法利用一个混乱的插入计划,利用局部统计测量和改变三维网格顶点,将水印插入到三维网格模型中。仿真结果表明,该算法具有较好的鲁棒性。带水印的三维网格模型能够抵抗相似变换、噪声添加、裁剪和网格平滑等攻击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A robust 3D mesh watermarking algorithm utilizing fuzzy C-Means clustering

A new robust 3D watermarking algorithm utilizing Fuzzy C-Means (FCM) clustering technique is presented. FCM clusters 3D mesh vertices into suitable and unsuitable choices to insert the watermark without occasioning visible deformation, and also it is tough for the attacker to determine places of the watermark insertion. Two watermarking processes are offered to insert the watermark into 3D mesh models. The first process utilizes topical statistical measurements like average and standard deviation in order to alter the values of vertices to secret watermark data into 3D mesh models, however, the second process utilizes a jumbled insertion planning to insert the watermark inside 3D mesh models utilizing the topical statistical measurements and altering 3D mesh vertices together. Simulation results show that the proposed algorithm is robust. The watermarked 3D mesh models are resistant to several attacks like similarity transforms, noise addition, cropping and mesh smoothing.

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