Rapid iris localization based on method of iterative pixel ratio to cirque area

CHENG Yu-qi; ZHU Ming; LI Gui-ju; GEI Wei; CHEN Yan-ping

doi:10.3788/OPE.20101810.2306

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Rapid iris localization based on method of iterative pixel ratio to cirque area

Article | 更新时间：2020-08-12

- Rapid iris localization based on method of iterative pixel ratio to cirque area
- Optics and Precision Engineering Vol. 18, Issue 10, Pages: 2306-2313(2010)
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,130033
  2. 中国科学院研究生院
  3. 长春工业大学电气与电子工程学院,吉林长春,130012
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20101810.2306
  CLC： TP391.4
- Received：10 November 2009，
  
  Revised：01 March 2010，
  
  Published Online：28 October 2010，
  
  Published：20 October 2010
- 稿件说明：
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程宇奇, 朱明, 李桂菊, 葛微, 陈彦平. 应用迭代圆环像素率法实现快速虹膜定位[J]. 光学精密工程, 2010,18(10): 2306-2313

CHENG Yu-qi, ZHU Ming, LI Gui-ju, GEI Wei, CHEN Yan-ping. Rapid iris localization based on method of iterative pixel ratio to cirque area[J]. Editorial Office of Optics and Precision Engineering , 2010,18(10): 2306-2313
程宇奇, 朱明, 李桂菊, 葛微, 陈彦平. 应用迭代圆环像素率法实现快速虹膜定位[J]. 光学精密工程, 2010,18(10): 2306-2313 DOI： 10.3788/OPE.20101810.2306.

CHENG Yu-qi, ZHU Ming, LI Gui-ju, GEI Wei, CHEN Yan-ping. Rapid iris localization based on method of iterative pixel ratio to cirque area[J]. Editorial Office of Optics and Precision Engineering , 2010,18(10): 2306-2313 DOI： 10.3788/OPE.20101810.2306.

摘要

针对虹膜定位易受噪声影响、速度慢、自适应性差等问题

提出了基于迭代圆环像素率法的快速虹膜定位算法。提出的定位算法包括切割虹膜图像、Hough圆检测粗定位、微积分算子精定位3个部分

从切割虹膜图像、图像抽样、迭代圆环像素率法、快速Hough圆检测以及分层定位思想5方面提高算法的速度。提出了缩小半径范围的迭代圆环像素率法以及消除瞳孔光斑的形态学方法

瞳孔分割阈值以及小范围的圆心、半径候选集等参数都是通过计算得到

自适应性好。使用4个虹膜数据库进行实验

并与相近算法进行了对比。实验结果表明

该算法的定位准确率为97.75%~99.07%

定位时间为52.847~158.502 ms

是一种鲁棒、快速、自适应的虹膜定位算法。

Abstract

Aimed at the problems of noise influence

high time consumption and bad adaptive performance for iris localization

a rapid iris localization algorithm based on the method of iterative pixel ratio to cirque area is proposed. The proposed method is composed of 3 parts: cutting iris image

coarse localization by circle detection of the Hough transformation and the precise localization by an integrodifferential operator. The methods of cutting the iris image

image sampling

iterative pixel ratio to cirque area

rapid circle detection of the Hough transformation and the layered localization theory are used to improve the algorithm speed. The method of iterative pixel ratio to cirque area is put forward to reduce the radius range

and the morphological method is used to eliminate the pupil faculae. The threshold of pupil segmentation

small-range candidates of circle centre and radius

etc

. are all obtained by the computation with good adaptive performance. Finally

four iris databases are applied in the experiments

and experimental results are compared with other algorithms. The results show that the accuracy of the proposed algorithm is 97.75%~99.07% and the time consumption is 52.847~158.502 ms. The experiments prove that the proposed method is a robust

rapid

adaptive iris localization algorithm with good comprehensive performance.

关键词

Keywords

references

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