Iris Recognition Based on Wavelet Transform and Neural Network
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.
Wang Anna Chen Yu Wu jie Zhangxinhua
School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
国际会议
北京
英文
762-765
2007-05-23(万方平台首次上网日期,不代表论文的发表时间)