Iris recognition based on wavelet transform and neural network

被引：1
|
作者：
Anna, Wang [1 ]
Yu, Chen [1 ]
Jie, Wu [1 ]
Zhang xin-hua [1 ]
机构：
[1] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110004, Peoples R China
来源：
2007 IEEE/ICME INTERNATIONAL CONFERENCE ON COMPLEX MEDICAL ENGINEERING, VOLS 1-4 | 2007年
关键词：
D O I：
10.1109/ICCME.2007.4381840
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
The biometric systems for user verification are becoming more popular in this age. Iris recognition system is a new technology for user verification. This paper presents an iris detection and recognition method, which adopts Canny transform to extract iris texture feature and wavelet probabilistic neural network as iris biometric classifier. The method combines wavelet neural network and probabilistic neural network for a new classifier model which will be able to improve the biometrics recognition accuracy as well as the global system performance. A simple and fast training algorithm, AdaBoost, is also introduced for training the wavelet probabilistic neural network. When applying the algorithm on an iris images database, the experimental results show 100% correct classifications and the method have an efficiency feasibility and performance.
引用
收藏
页码：758 / 761
页数：4
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