An image segmentation based method for iris feature extraction

作     者：XU Guang-zhu ZHANG Zai-feng MA Yi-de 

作者机构：The College of Electrical Engineering and Information Technology China Three Gorges University Yichang 443002 China School of Information Science and Engineering Lanzhou University Lanzhou 730000. China 

出 版 物：《The Journal of China Universities of Posts and Telecommunications》 (中国邮电高校学报（英文版）)

年 卷 期：2008年第15卷第1期

页      面：96-101,117页

核心收录：

学科分类：0810[工学-信息与通信工程] 1205[管理学-图书情报与档案管理] 0839[工学-网络空间安全] 081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：the National Natural Science Foundation of China(6057201) the 985 Special Study Project of Lanzhou University Foundation(LZ985-231-58262-7) 

主　　题：iris recognition image segmentation ICM 

摘      要：In this article, the local anomalistic blocks such as crypts, furrows, and so on in the iris are initially used directly as iris features. A novel image segmentation method based on intersecting cortical model （ICM） neural network was introduced to segment these anomalistic blocks. First, the normalized iris image was put into ICM neural network after enhancement. Second, the iris features were segmented out perfectly and were output in binary image type by the ICM neural network. Finally, the fourth output pulse image produced by ICM neural network was chosen as the iris code for the convenience of real time processing. To estimate the performance of the presented method, an iris recognition platform was produced and the Hamming Distance between two iris codes was computed to measure the dissimilarity between them. The experimental results in CASIA v1.0 and Bath iris image databases show that the proposed iris feature extraction algorithm has promising potential in iris recognition.