Image-Moment Based Affine Invariant Watermarking Scheme Utilizing Neural Networks  

作　　者：吴健珍 谢剑英 杨煜普 

机构地区：[1]Department of Automation, Shanghai Jiaotong University, Shanghai 200030, China

出　　处：《Journal of Beijing Institute of Technology》2006年第1期71-75,共5页北京理工大学学报（英文版）

基　　金：theNational"863"ProgramProject(2001AA422420-02)

摘　　要：A new image watermarking scheme is proposed to resist rotation, scaling and translation （RST） attacks. Six combined low order image moments are utilized to represent image information on rotation, scaling and translation. Affine transform parameters are registered by feedforward neural networks. Watermark is adaptively embedded in discrete wavelet transform （DWT） domain while watermark extraction is carried out without original image after attacked watermarked image has been synchronized by making inverse transform through parameters learned by neural networks. Experimental results show that the proposed scheme can effectively register affine transform parameters, embed watermark more robustly and resist geometric attacks as well as JPEG2000 compression.A new image watermarking scheme is proposed to resist rotation, scaling and translation （RST） attacks. Six combined low order image moments are utilized to represent image information on rotation, scaling and translation. Affine transform parameters are registered by feedforward neural networks. Watermark is adaptively embedded in discrete wavelet transform （DWT） domain while watermark extraction is carried out without original image after attacked watermarked image has been synchronized by making inverse transform through parameters learned by neural networks. Experimental results show that the proposed scheme can effectively register affine transform parameters, embed watermark more robustly and resist geometric attacks as well as JPEG2000 compression.

关 键 词：digital watermark affine transform geometric attacks image moment neural networks 

分 类 号：TP309[自动化与计算机技术—计算机系统结构] TP183[自动化与计算机技术—计算机科学与技术]