一种快速有效的虹膜定位方法
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摘要
虹膜定位是虹膜识别系统中的一个重要步骤,后续处理步骤均取决于其准确性。针对传统虹膜定位方法的局限性,设计了一种由粗到精的算法,解决计算成本问题的同时达到可接受的精度要求。利用灰度投影法和自适应阈值将虹膜图像转换为二值图像实现虹膜内边界的粗定位,再用Canny算子对边缘进行检测精定位,然后根据定位结果结合矩形检测模板对外边界进行粗定位,使用Daugman圆盘算子检测虹膜外边界进行精定位。实验结果表明该算法能准确快速地定位虹膜区域。
Iris localization is an important step in the iris recognition system,whose speed and accuracy affect all the subsequent processing steps.In view of the limitations of traditional iris localization methods,a coarse to fine algorithm is designed to solve the computational cost and attain admissibility accuracy.It employs gray projection algorithm and uses an adaptive threshold to convert the iris image into a binary image to achieve coarse positioning of the inner boundary of the iris,and then it uses the Canny operator to perform fine positioning of the iris inner boundary.According to the positioning results of the inner boundary of the iris,the outer boundary of the rectangle detection template is coarsely positioned.Daugman's disc operator is used to detect the outer boundary of the iris to precisely locate the outer boundary.The experimental results show that the algorithm can accurately and quickly locate the iris region.
Iris localization is an important step in the iris recognition system,whose speed and accuracy affect all the subsequent processing steps.In view of the limitations of traditional iris localization methods,a coarse to fine algorithm is designed to solve the computational cost and attain admissibility accuracy.It employs gray projection algorithm and uses an adaptive threshold to convert the iris image into a binary image to achieve coarse positioning of the inner boundary of the iris,and then it uses the Canny operator to perform fine positioning of the iris inner boundary.According to the positioning results of the inner boundary of the iris,the outer boundary of the rectangle detection template is coarsely positioned.Daugman's disc operator is used to detect the outer boundary of the iris to precisely locate the outer boundary.The experimental results show that the algorithm can accurately and quickly locate the iris region.
引文
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[2]李海青,孙哲南,谭铁牛,等.虹膜识别技术进展与趋势[J].信息安全研究,2016(1):40-43.
[3]史春蕾,杨丹丹,韩飞.虹膜识别综述[J].科技展望,2016(5):307-308.
[4]尚睿.虹膜识别技术的最新进展综述[J].电脑知识与技术,2015,11(22):117-118.
[5]秦武旻,朱长婕.虹膜快速检测与精确定位的算法研究[J].国外电子测量技术,2017,36(4):25-28.
[6]陈传虎,邹德旋,刘海宽.应用统计距离实现虹膜定位[J].光学精密工程,2012,20(11):2516-2522.
[7]DAUGMAN J.High confidence visual recognition of persons by a test of statistical independence[J].IEEE Transactions on Pattern Analysis and Machine Intelligence.1993,15(11):1148-1161.
[8]WILDES R P.Iris recognition:an emerging biometric technology[J].Proceedings of the IEEE.1997,85(9):1348-1363.
[9]MASEK L.Recognition of human iris patterns for biometric identification[D].Perth:The University of Western Australia,2003.
[10]叶学义,庄镇泉,张云超.一种快速新颖的虹膜定位算法[J].计算机工程与应用,2003,39(30):54-56.
[11]苑玮琦,林忠华,徐露.一种基于人眼结构特征的新颖虹膜定位算法[J].光电工程,2007,34(1):112-116.
[12]王虹,曾文.一种改进的虹膜定位算法研究[J].武汉理工大学学报,2008,30(6):846-848.
[13]孙彩堂,周春光,刘向东,等.一种改进的虹膜定位方法[J].小型微型计算机系统,2006,27(7):1335-1338.
[14]贺国旗,凌凤彩,林晓.基于Canny思想的Robinson边缘检测算法[J].计算机工程与科学,2016,38(4):755-760.
[15]吕康东.虹膜快速定位及特征提取算法的研究[D].包头:内蒙古科技大学,2017.
[16]许妍.虹膜定位及识别算法的研究与改进[D].兰州:西北师范大学,2016.
[17]潘胜男.虹膜识别前处理算法的研究[D].长春:吉林大学,2017.
[18]DAUGMAN J.Statistical richness of visual phase information:update on recognizing persons by iris patterns[J].International Journal of Computer Vision,2001,45(1):25-38.
[19]DAUGMAN J.High confidence recognition of persons by iris patterns[C].International Carnahan Conference on Security Technology,2001:254-263.
[20]中国科学院化学研究所.CASIA虹膜图像数据库[EB/OL].http://www.sinobiometrics.com,2003.
[21]彭建,向军.一种基于形态学的虹膜定位快速算法[J].计算机工程与应用,2012,48(4):193-196.