多分辨率滤波在手背血管特征提取中的应用

Application of Multiresolutional Filter On Feature Extraction of Palm-Dorsa Vein Patterns

人体手背血管识别是一门新兴的生物特征识别技术,提出了这种生物特征提取的一种算法.它利用分水岭算法提取出带有纹理特征信息的特征点FPVP(feature points of vein pattern);针对FPVP的不同的特征信息采用二阶矩和统计的方法进行多分辨率滤波得到DP(dominant points),每个DP都是多维的向量,用所有‖DP‖组成手背血管的特征向量;最后使用相关算法针对来自53个手背血管的265个样本进行了特征相关匹配实验,其最小错误率仅为4.31%.

Recognition of palm-dorsa vein paper presents a new algorithm for extracting patterns is a new biometric identification technology. The such patterns. In the algorithm watershed transformation is firstly used to extract Feature Points of Vein Pattern （FPVP） from the image of palm-dorsa vein pattern. Feature Points of Vein Pattern are then upgraded into Dominant Points with moment filter and count filter for different feature information of FPVP. Every Dominant Point is a multidimensional vector of and the 2-norms of all DPs in an image constitute the feature vector of the vein pattern. In the end the feasibility of extracting feature of palm-dorsa vein pattern is evaluated by performing the matching test of samples with a correlation method. The dataset is of 265 samples from 53 vein patterns, and the minimum verification error rate is about 4.31%.