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基于二次圆周补偿的虹膜边界定位方法

Iris Boundary Localization Method Based on Double Circular Compensation

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摘要

为提高虹膜定位的准确性与实时性, 提出了基于二次圆周补偿的虹膜边界定位算法。所提算法以近似半径补偿与近似圆心补偿为核心, 对虹膜内及其外边缘进行定位。定位内边界时, 利用最小灰度均值法进行粗定位, 并在提取内边缘图像后采用近似圆心补偿法进行细定位; 定位外边界时, 采用近似半径补偿法进行粗定位, 再根据近似圆心补偿法进行细定位。实验结果表明, 从CASIA虹膜库中随机选取了2000张不同虹膜图像进行了验证, 算法平均定位时间为0.29 s, 定位准确率为98.1%。所提算法在准确度与实时性方面都较对比方法有所提高。

Abstract

In order to improve the accuracy and real-time performance of iris location, an iris boundary location algorithm based on double circular compensation is proposed. The approximate radius compensation and approximate circle center compensation are used as the core to locate the inner and outer boundary of the iris by the proposed algorithm. When locating the inner boundary, the minimum gray average method is used to perform coarse localization, and the approximate circle center compensation method is used for locating the inner boundary exactly after extracting the inner boundary images. When locating the outer boundary, the approximate radius compensation method is used to perform coarse locating, and the exact locating is performed by the approximate circle center compensation method. Experimental results show that 2000 different iris images from CASIA for verification are randomly selected. The average locating time of the algorithm was 0.29 s, and the locating accuracy rate is 98.1%. The proposed algorithm is more accurate and faster than the contrast method.

Newport宣传-MKS新实验室计划
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中图分类号:TP391.41

DOI:10.3788/lop55.101505

所属栏目:机器视觉

基金项目:吉林省科技发展计划重点研发项目(20180201025GX)

收稿日期:2018-03-09

修改稿日期:2018-04-18

网络出版日期:2018-05-25

作者单位    点击查看

薛雅迪:长春理工大学光电工程学院, 吉林 长春 130022
王劲松:长春理工大学光电工程学院, 吉林 长春 130022
樊纯璨:长春理工大学光电工程学院, 吉林 长春 130022

联系人作者:王劲松(soldier_1973@163.com)

【1】Han M, Peng Y H, Zhang S L, et al. Iris recognition based on empirical mode decomposition[J]. Acta Optica Sinica, 2010, 30(2): 364-368.
韩民, 彭玉华, 张顺利, 等. 基于经验模态分解的虹膜识别[J]. 光学学报, 2010, 30(2): 364-368.

【2】Zhou L, Chi Y D, Guo L. Optical system design of object-telecentric dual finger fingerprint scanner[J]. Laser & Optoelectronics Progress, 2016, 53(10): 102201.
周路, 迟耀丹, 郭亮. 物方远心双指指纹采集光学系统设计[J]. 激光与光电子学进展, 2016, 53(10): 102201.

【3】Xia J, Pei D, Wang Q Z, et al. Face recognition based on local adaptive ternary derivative pattern coupled with Gabor feature[J]. Laser & Optoelectronics Progress, 2016, 53(11): 111004.
夏军, 裴东, 王全州, 等. 融合Gabor特征的局部自适应三值微分模式的人脸识别[J]. 激光与光电子学进展, 2016, 53(11): 111004

【4】Daugman J. How iris recognition works[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2004, 14(1): 21-30.

【5】Wildes R P. Iris recognition: an emerging biometric technology[J]. Proceedings of the IEEE, 1997, 85(9): 1348-1363.

【6】Wu J H, Zou D X, Li J H. Iris location algorithm based on small-scale searching[J]. Chinese Journal of Scientific Instrument, 2008, 29(8): 1704-1708.
吴建华, 邹德旋, 李静辉. 基于小范围搜索的虹膜定位方法[J]. 仪器仪表学报, 2008, 29(8): 1704-1708.

【7】Li Y, Li W, Ma Y D. Accurate iris location based on region of interest[C]∥Proceedings of IEEE International Conference on Biomedical Engineering and Biotechnology, 2012: 704-707.

【8】Zou D X, Wang X, Chen C H, et al. Iris location algorithm based on improved particle swarm optimization[J]. Optics and Precision Engineering, 2014, 22(4): 1056-1063.
邹德旋, 王鑫, 陈传虎, 等. 基于改进粒子群的虹膜定位算法[J]. 光学 精密工程, 2014, 22(4): 1056-1063.

【9】Wang Y X, Liu T G, Jiang J F. Rapid iris localization algorithm based on image sampling[J]. Opto-Electronic Engineering, 2008, 35(9): 122-126.
王云新, 刘铁根, 江俊峰. 基于图像抽样的快速虹膜定位算法[J]. 光电工程, 2008, 35(9): 122-126.

【10】Ma Y D, Zhou L J, Li Y. Iris location algorithm by vector field convolution[J]. Infrared and Laser Engineering, 2014, 43(10): 3497-3503.
马义德, 周丽君, 李园. 基于矢量场卷积的虹膜定位[J]. 红外与激光工程, 2014, 43(10): 3497-3503.

引用该论文

Xue Yadi,Wang Jinsong,Fan Chuncan. Iris Boundary Localization Method Based on Double Circular Compensation[J]. Laser & Optoelectronics Progress, 2018, 55(10): 101505

薛雅迪,王劲松,樊纯璨. 基于二次圆周补偿的虹膜边界定位方法[J]. 激光与光电子学进展, 2018, 55(10): 101505

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