摘要
以回归型支持向量机(SVR)理论基础,提出了一种可有效抵抗几何攻击的图像水印检测新算法.该算法首先选取图像的组合矩作为特征向量,并通过SVR对旋转、缩放、平移等几何变换参数进行训练学习,以获得SVR训练模型;然后利用SVR训练模型对待检测图像进行数据预测,并结合预测输出结果对其进行几何校正;最后从已校正数字图像内提取出水印信息.仿真实验结果表明,本文算法对常规信号处理(滤波、叠加噪声、JPEG压缩等)和几何攻击(旋转、缩放、平移、剪切等)
In this paper, a robust image watermarking detection based on support vector regression (SVR) is proposed. Firstly, six combined low order image moments are taken as the feature vector and the geometric transformation parameters are regarded as the training objective, the appropriate kernel function is selected for the training, and a SVR training model can be obtained. Secondly, the combined moments for test image are selected as input vector, the actual output is predicted by using the well trained SVR, and the geometric correction is performed on the test image by using the obtained geometric transformation parameters. Finally, the digital watermark is extracted from the corrected test image. Experimental results show that the proposed watermarking detection algorithm is not only robust against common signals processing such as filtering, sharpening, noise adding, JPEG compression etc, but also robust against the geometric attacks such as rotation, translation, scaling, cropping, combination attacks, etc.
出处
《中国图象图形学报》
CSCD
北大核心
2009年第6期1131-1135,共5页
Journal of Image and Graphics
基金
国家自然科学基金项目(60773031
60873222)
计算机软件新技术国家重点实验室(南京大学)开放基金项目(A200702)
信息安全国家重点实验室(中国科学院软件研究所)开放基金项目(03-06)
大连市科技基金项目(2006J23JH020)
江苏省计算机信息处理技术重点实验室(苏州大学)开放课题基金项目(KJS0602)
图像处理与图像通信"江苏省重点实验室(南京邮电大学)开放基金项目(ZK205014)
辽宁省教育厅高等学校科研项目(2008351)
关键词
数字水印
几何攻击
回归型支持向量机
几何校正
digital watermarking, geometric attacks, support vector regression, geometric correction