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

作　　者：GAO Guang-yong JIANG Guo-ping 

机构地区：[1]Center for Control & Intelligence Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, China [2]School of Information Science & Technology, Jiujiang University, Jiujiang 332005, China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2011年第2期94-101,共8页中国邮电高校学报（英文版）

基　　金：supported by the National Natural Science Foundation of China (60874091);the Six Projects Sponsoring Talent Summits of Jiangsu Province (SJ209006);the Natural Science Basic Research Project for Universities of Jiangsu Province (08KJD510022);the Natural Science Foundation of Jiangsu Province (BK2010526)

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.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：Tchebicbef moment invariants composite chaos SVR zero-bit watermarking 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP183[自动化与计算机技术—计算机科学与技术]