首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于多特征描述的指横纹识别
引用本文:张延强,孙冬梅,裘正定.基于多特征描述的指横纹识别[J].北方交通大学学报,2011(2):8-13.
作者姓名:张延强  孙冬梅  裘正定
作者单位:北京交通大学计算机与信息技术学院,北京100044
基金项目:国家自然科学基金资助项目(60773015); 北京市自然科学基金资助项目(4102051); 中央高校基本科研业务费专项资金资助(2009JBZ006)
摘    要:提出一种基于多特征描述的指横纹识别方法.分别提取指横纹的主成分特征、Gabor相位特征和Gabor幅值特征构成识别系统,采用Fisher线性判决方法融合各自匹配分数,进一步提高系统性能.通过98个人、1 971幅图像的测试实验表明,本文方法在获得较高性能的同时(识别率为99.39%,平均错误率为0.56%),单次匹配时间仅为0.67 ms,可以满足中等规模数据库实时识别要求.

关 键 词:指横纹  主成分分析  2D  Gabor滤波  匹配分数融合

Knuckleprint authentication using multiple representations
ZHANG Yanqiang,SUN Dongmei,QIU Zhengding.Knuckleprint authentication using multiple representations[J].Journal of Northern Jiaotong University,2011(2):8-13.
Authors:ZHANG Yanqiang  SUN Dongmei  QIU Zhengding
Institution:(School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044,China)
Abstract:A novel knuckleprint authentication method is proposed by using multiple representations.Principle component analysis(PCA) features,2D Gabor phase features and magnitude features are extracted for knuckleprint authentication.Fisher criterion based linear discrimination analysis(LDA) is used for match-score fusion,which can further improve the system performance.Experiments based on the database that contains 1 971 image samples from 98 individuals demonstrate that the high recognition accuracy and efficient performance can be achieved with the proposed algorithm.The recognition rate is 99.39%,and the half total error rate(HTER) is no more than 0.56% and one match time consumption reaches 0.67 ms.
Keywords:knuckleprint  principle component analysis  2D Gabor filter  score-level fusion
本文献已被 维普 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号