数字水印检测的SVM算法及其测试

SVM Algorithm for Digital Watermarking Detection and Testing

根据Vapnik等人提出的一种基于统计学习理论的机器学习算法,在水印检测技术中引入一种针对小样本的学习理论SVM算法.此算法能够实现结构风险最小化,避免了以往检测方法中依赖于特定的嵌入算法的缺点.建立了数字水印检测的SVM算法的测试平台,研究了平台的组成模块和功能.实验表明使用SVM进行水印检测能实现与嵌入算法的无关性,能有效提高检测效率,为数字图像水印的检测提供了一种新方法.

SVM, proposed by Vapnik and others, is a machine algorithm based on statistical theories. In this paper, as the theory directing at minor samples, the applied aspects of SVM algorithm in watermarking detection are concerned. This algorithm can realize the structural risk minimization and be free from the disadvantages in correlation detection algorithm that depends on the special embedding algorithm. SVM-oriented detecting platform is set up, its models and functions are discussed. The test shows that SVM algorithm is independent with embedding algorithm. It can promote watermarking detection efficiency and give a new method for digital watermarking detection technology.