多矢量曲线水印检测的SVM分类融合方法

针对矢量图形的版权保护问题,提出了一种基于SVM分类融合的多矢量曲线水印检测方法。该方法在水印嵌入阶段,对多条曲线嵌入由嵌入密钥生成的水印;在检测阶段,对多条曲线检测由检测密钥生成的水印,同时多条曲线的检测相关值按一定的顺序构成一个特征向量;然后由SVM两类别分类器对该特征向量进行决策,以判定这多条曲线是否嵌入了由检测密钥生成的水印。SVM分类器的学习样本是模仿各种多矢量曲线变换和攻击下,相应产生了由多曲线检测相关值构成的特征向量。该方法本质上是基于SVM分类的多个检测相关值的融合方法。理论分析和仿真结果证明,该方法是可行的和有效的。

Watermark Detection of Vector Curves Using SVM Classification Fusion Method

In order to protect the copyright of the vector graphics,in this paper we introduce a fusion rule for watermark detection of vector curves using SVM classification. At the embedding stage,the watermarks are embedded into multi vector curves with the same key. At the detecting stage,firstly,the watermarks are detected using the embedded key then a eigenvector is obtained which is created by detection correlative values in a certain order. Finally the SVM classification can determine whether those curves have the watermarks that embedded with a right key. The study samples of SVM classification are imitating all kinds of eigenvector,which are detected from the attacked and transformed curves. Essentially it is a fusion rule of multi related values,which based on the SVM classification. Theoretical analysis and simulation results prove it is feasible and effective.