Iris recognition based on probabilistic features

被引：0

作者：

Liu, Zhaojun ^{[1
,2
]}

Li, Xiongfei ^{[1
,2
]}

Zhao, Zhenting ^{[3
]}

机构：

[1] Key Laboratory of Symbolic Computation and Knowledge Engineering for Ministry of Education, Jilin University, Changchun

[2] College of Computer Science and Technology, Jilin University, Changchun

[3] College of Software, Jilin University, Changchun

来源：

Journal of Computational Information Systems | 2014年 / 10卷 / 20期

关键词：

Iris recognition; Iris regmentation; Log gabor transform; Probabilistic features;

D O I：

10.12733/jcis11958

中图分类号：

学科分类号：

摘要：

In this paper, we propose an iris recognition algorithm based on probabilistic features. At the image preprocessing step, we do many experiments on iris segmentation in order to minimize the negative influence on recognition caused by eyelash and eyelid. As different segmentation angle has different results, we have determined an ideal angle for further recognition. At the recognition step, iris is transformed into frequency domain by using Log Gabor filters. Then raw features are extracted. Probabilistic features, with two forms of distribution, random distribution and normal distribution, are set of vectors generated from these raw features. At the matching step, the raw features are replaced by the property features. KNN algorithm is used to decide the final result. Experiment results showed that the proposed method can make further improvement of recognition rates and reduce the time consumption significantly. 1553-9105/Copyright © 2014 Binary Information Press

引用

页码：8783 / 8792

页数：9

共 14 条

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