Zero-bit watermarking resisting geometric attacks based on composite-chaos optimized SVR model

doi:10.1016/S1005-8885(10)60050-7

中国邮电高校学报(英文) ›› 2011, Vol. 18 ›› Issue (2): 94-101.doi: 10.1016/S1005-8885(10)60050-7

• Artificial Intelligence • 上一篇下一篇

Zero-bit watermarking resisting geometric attacks based on composite-chaos optimized SVR model

高光勇¹,¹,²,蒋国平²

1.
2. 南京邮电大学

收稿日期:2010-08-20 修回日期:2010-11-15 出版日期:2011-04-30 发布日期:2011-04-15
通讯作者: 蒋国平 E-mail: jianggp@njupt.edu.cn
基金资助:
国家自然科学基金;国家教育部新世纪优秀人才支持计划;江苏省‘六大人才高峰’高层次人才项目

Zero-bit watermarking resisting geometric attacks based on composite-chaos optimized SVR model

Received:2010-08-20 Revised:2010-11-15 Online:2011-04-30 Published:2011-04-15
Contact: JIANG Guo-ping E-mail: jianggp@njupt.edu.cn
Supported by:
;the Program for New Century Excellent Talents in University of China;the Six Projects Sponsoring Talent Summits of Jiangsu Province

摘要/Abstract

摘要：

The problem to improve the performance of resisting geometric attacks in digital watermarking is addressed in this paper. Based on the optimized support vector regression (SVR), a zero-bit watermarking algorithm is presented. The proposed algorithm encrypts the watermarking image by using composite chaos with large key space and capacity against prediction, which can strengthen the safety of the proposed algorithm. By using the relationship between Tchebichef moment invariants of detected image and watermarking characteristics, the SVR training model optimized by composite chaos enhances the ability of resisting geometric attacks. Performance analysis and simulations demonstrate that the proposed algorithm herein possesses better security and stronger robustness than some similar methods.

关键词:

Tchebichef moment invariants, composite chaos, SVR, zero-bit watermarking

Abstract:

Key words:

Tchebichef moment invariants, composite chaos, SVR, zero-bit watermarking

中图分类号:

TP393

参考文献

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Zero-bit watermarking resisting geometric attacks based on composite-chaos optimized SVR model

Zero-bit watermarking resisting geometric attacks based on composite-chaos optimized SVR model

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