一种手臂静脉特征提取与匹配的算法  

An Algorithm for Feature Extraction and Matching of Arm Veins

作　　者：陈晓腾 王彪[1] 唐超颖[1] 苏菡[2] 魏祥灰 CHEN Xiao-teng;WANG Biao;TANG Chao-ying;SU Han;WEI Xiang-hui(College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing,Jiangsu 211106,China;School of Computer Seience,Sichuan Normal Unviersity,Chengdu,Sichuan 610101,China)

机构地区：[1]南京航空航天大学自动化学院,江苏南京211106 [2]四川师范大学计算机科学学院,四川成都610101

出　　处：《计算技术与自动化》2018年第3期100-105,共6页Computing Technology and Automation

基　　金：国家自然科学基金资助项目(61403196;61403266);南京航空航天大学研究生创新基地(实验室)开放基金资助(kfjj20170302);中央高校基本科研业务费专项资金资助

摘　　要：针对手臂静脉这一全新的生物特征提出一种特征提取及匹配的算法。首先利用限制对比度自适应直方图均衡化方法对近红外图像进行对比度调整,接着利用Gabor滤波器提取静脉,并进行方向和尺度的标准化;在曲线修复和分割的基础上,提取描述曲线段的方向特征、位置特征和描述曲线形状的Hu不变矩特征;然后搜索匹配曲线对,并利用粒子群算法计算最优空间变换关系,最后进行静脉的匹配。针对150人数据库的匹配实验结果表明,该算法的识别率优于其他方法,说明手臂静脉作为一种新的生物特征具有良好的应用前景。A feature extraction and matching algorithm is proposed for arm veins. Firstly, the contrast of near infrared （NIR） images is adjusted using the contrast limited adaptive histogram equalization （CLAHE） method. Then the Gabor filters are adopted to extract veins. The orientation and scale of veins are normalized, and the renovation and segmentation of veins are performed. For each curve segment, the direction, position and Hu invariant moment features are extracted. Matching curve pairs are searched, and the optimal space transformation is calculated using the particle swarm optimization （PSO） method. Finally the veins are matched. The algorithm is evaluated in a database of arm vein images collected from 150 people. The experimental results show that the matching accuracy is better than other methods, which indicates that arm veins owe a good application prospect.

关 键 词：生物特征 手臂静脉 粒子群优化 识别 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]