A blind fragile watermarking for 3D triangular model based on curvature features and chaos sequence

kariman mamdouh, N. Semary, Hatem Ahmed
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Abstract

Noura A.Semarya,Kariman M.Mabrouka,, Hatem Abdul-Kaderb a Information Technology dept., Faculty of Computers and Information, Menoufia University, Menoufia 32511, Egypt b Information system dept., Faculty of Computers and Information, Menoufia University, Menoufia 32511, Egypt kariman.mamdouh@ci.menofia.edu.eg Abstract 3D models unauthorized modification is an attractive research problem nowadays due to the widespread availability of technologies and designs on the internet. In this paper, we propose a blind fragile watermarking scheme in the spatial domain for 3D model authentication based on the curvature features of the 3D model and chaos sequence. First, we compute the curvature feature for every vertex of the 3D model, after that, the vertices are classified into 3 classes: flat, peak, and In-between vertices using K-means clustering algorithm. We suggested two methods for embedding the watermark based on the least significant bit (LSB) substitution technique; Cluster Type-based Embedding (CTE) and Cluster Size-based Embedding (CSE). The proposed methods employ a Chaos sequence generator to generate a Chaos sequence that is used to generate the embedded watermark, where the tampering region can be verified and located by the Chaos sequence-based watermark check. Many assessment methods are employed to evaluate the proposed method with various unauthorized attacks like rotation, translation, scaling, cropping, and noise addition. The experiment results show an improvement of embedding imperceptibility as well as tempered regions detection compared to existing literature works.
基于曲率特征和混沌序列的三维三角形模型脆弱盲水印
Noura a. semarya,Kariman M.Mabrouka, Hatem Abdul-Kaderb a Menoufia大学计算机与信息学院信息技术系,埃及Menoufia 32511 b Menoufia大学计算机与信息学院信息系统系,埃及Menoufia 32511 kariman.mamdouh@ci.menofia.edu.eg摘要由于互联网上技术和设计的广泛可用性,未经授权的3D模型修改是当今一个有吸引力的研究问题。本文提出了一种基于三维模型曲率特征和混沌序列的空间域脆弱盲水印方案。首先,我们计算三维模型的每个顶点的曲率特征,然后使用K-means聚类算法将顶点分为3类:平面顶点、峰值顶点和中间顶点。提出了两种基于LSB替换技术的水印嵌入方法;CTE (Cluster Type-based Embedding)和CSE (Cluster Size-based Embedding)。该方法利用混沌序列发生器生成用于生成嵌入水印的混沌序列,通过基于混沌序列的水印检测来验证和定位嵌入水印的篡改区域。针对旋转、平移、缩放、裁剪、加噪等各种未经授权的攻击,采用了多种评估方法对所提出的方法进行评估。实验结果表明,与现有文献相比,该方法在嵌入不可感知性和缓和区域检测方面都有所提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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