[1]张震张英杰.基于支持向量机与Hamming距离的虹膜识别方法[J].郑州大学学报(工学版),2015,36(03):25-29.[doi:10.3969/ j.issn.1671 -6833.2015.03.006]
　ZHANG Zhen,ZHANG Ying-jie.Iris Recognition Method Based on Support Vector Machine and Hamming Distance[J].Journal of Zhengzhou University (Engineering Science),2015,36(03):25-29.[doi:10.3969/ j.issn.1671 -6833.2015.03.006]
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基于支持向量机与Hamming距离的虹膜识别方法()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
36卷
期数:
2015年03期
页码:
25-29
栏目:
出版日期:
2015-06-30

文章信息/Info

Title:
Iris Recognition Method Based on Support Vector Machine and Hamming Distance
作者:
张震1张英杰2
郑州大学电气工程学院,河南郑州450001
Author(s):
ZHANG Zhen; ZHANG Ying-jie
School of Electrical Engineering,Zhengzhou University,Zhengzhou 450001,China
关键词:
虹膜识别; 支持向量机;  Hamming 距离;  Log-Gabor滤波器
Keywords:
iris recognition; support vector machine;  hamming distance; Log-Gabor filter
分类号:
TP391
DOI:
10.3969/ j.issn.1671 -6833.2015.03.006
文献标志码:
A
摘要:
针对传统的虹膜识别方法侧重于特征提取这一现象,提出了一种侧重于模式匹配的识别算法，即基于支持向量机(Support Vector Machine,SVM)和 Hamming距离的虹膜识别方法.该算法首先对采集到的虹膜图像进行预处理,准确定位出虹膜,并对其进行归一化处理;然后使用Log-Gabor滤波器提取虹膜纹理特征,在得到虹膜特征编码后,用SVM和 Hamming 距离方法进行模式匹配.在CASIA 虹膜库上的实验结果表明:与经典的识别方法相比,该方法识别率达到了99.63% ,错误接受率(FAR)和错误拒绝率(FRR)分别降到了0.02%和0.35% .
Abstract:
In order to solve the problem of traditional iris recognitions focusing on feature extraction,a newmethod focusing on pattern matching was proposed,which was named iris recognition method using supportvector machine ( SVM) and Hamming distance.Firstly,normalization was used to process the iris positionwhich was located in the eye images.And then Log-Gabor filter was used to extract the features. After obtai-ning iris feature codes,SVM and Hamming distance were used to classify the iris features. Experiment resultson the CASIA iris database showed that recognition rate of this method reached 99.63%,false acceptance rateand false rejection rate were reduced to 0.02% and 0.35% compared to the classical recognition methods.

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