Iris Recognition Based on Wavelet Transform and Neural Network

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.

作者: Wang Anna Chen Yu Wu jie Zhangxinhua

作者单位: School of Information Science and Engineering, Northeastern University, Shenyang 110004, China

会议类型: 国际会议

会议名称: 2007 IEEE/ICME International Conference on Complex Medical Engineering-CME2007(CME2007 第二届国际复合医学工程学术大会)

会议地点: 北京

会议语种:英文

页码: 762-765

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）