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CLC number: TP391.41

On-line Access: 2014-05-06

Received: 2013-10-24

Revision Accepted: 2014-02-14

Crosschecked: 2014-04-11

Cited: 17

Clicked: 3700

Citations:  Bibtex RefMan EndNote GB/T7714

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Journal of Zhejiang University SCIENCE C 2014 Vol.15 No.5 P.351-362


A blind watermarking algorithm for 3D mesh models based on vertex curvature

Author(s):  Yong-zhao Zhan, Yan-ting Li, Xin-yu Wang, Yi Qian

Affiliation(s):  School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China

Corresponding email(s):   yzzhan@ujs.edu.cn

Key Words:  Three-dimensional mesh model, Visual masking, Root mean square curvature, Blind watermarking, Attack resisting

Yong-zhao Zhan, Yan-ting Li, Xin-yu Wang, Yi Qian. A blind watermarking algorithm for 3D mesh models based on vertex curvature[J]. Journal of Zhejiang University Science C, 2014, 15(5): 351-362.

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author="Yong-zhao Zhan, Yan-ting Li, Xin-yu Wang, Yi Qian",
journal="Journal of Zhejiang University Science C",
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%T A blind watermarking algorithm for 3D mesh models based on vertex curvature
%A Yong-zhao Zhan
%A Yan-ting Li
%A Xin-yu Wang
%A Yi Qian
%J Journal of Zhejiang University SCIENCE C
%V 15
%N 5
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%@ 1869-1951
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1300306

T1 - A blind watermarking algorithm for 3D mesh models based on vertex curvature
A1 - Yong-zhao Zhan
A1 - Yan-ting Li
A1 - Xin-yu Wang
A1 - Yi Qian
J0 - Journal of Zhejiang University Science C
VL - 15
IS - 5
SP - 351
EP - 362
%@ 1869-1951
Y1 - 2014
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C1300306

We propose a robust blind watermarking algorithm for three-dimensional (3D) mesh models based on vertex curvature to maintain good robustness and improve visual masking in 3D mesh models. In the embedding process, by using the local window of vertex, the root mean square curvature is calculated for every vertex of the 3D mesh model and an ordered set of fluctuation values is obtained. According to the ordered fluctuation values, the vertices are separated into bins. In each bin the fluctuation values are normalized. Finally, the mean of the root mean square curvature fluctuation values of the vertices in each bin is modulated to embed watermark information. In watermark detection, the algorithm uses a blind watermark extraction technique to extract the watermark information. The experimental results show that the algorithm has a very good performance for visual masking of the embedded model and that it can resist a variety of common attacks such as vertex rearrangement, rotation, translating, uniform scaling, noise, smoothing, quantization, and simplification.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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