虹膜图像的质量评价研究

史春蕾; 周凤文; 胡雨露; 孙海江

doi:10.3788/YJYXS20163112.1131

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虹膜图像的质量评价研究

显示与图像 | 更新时间：2020-07-07

- 虹膜图像的质量评价研究
- Study for iris image quality assessment
- 液晶与显示 2016年31卷第12期页码：1131-1136
- 作者机构：
  
  1.长春师范大学物理学院, 吉林长春 130032
  2.长春理工大学教务处, 吉林长春 130022
  3.东北师范大学物理学院, 吉林长春 130000
  4.中国科学院长春光学精密机械与物理研究所图像处理技术研究部, 吉林长春 130033
- 作者简介：
  
  史春蕾(1983-), 女, 吉林长春人, 博士, 讲师, 2011年于中科院长春光机所获得博士学位, 现为长春师范大学教师, 主要从事图像处理方面的研究。E-mail:scl-83218@163.com
- 基金信息：
  
  吉林省教育厅“十二五”科学技术研究项目(2015359);长春师范大学实验教学改革研究项目;Supported by "Twelfth Five-Year" Science and Technology Research Project of the Education Department of Jilin Province(2015359);Experiment teaching reformation research project of Changchun Normal University
- DOI：10.3788/YJYXS20163112.1131
  中图分类号： TP391.4
- 收稿日期：2016-11-07，
  
  录用日期：2016-12-5，
  
  纸质出版日期：2016-12-05
- 稿件说明：
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史春蕾, 周凤文, 胡雨露, 等. 虹膜图像的质量评价研究[J]. 液晶与显示, 2016,31(12):1131-1136.

Chun-lei SHI, Feng-wen ZHOU, Yu-lu HU, et al. Study for iris image quality assessment[J]. Chinese journal of liquid crystals and displays, 2016, 31(12): 1131-1136.
史春蕾, 周凤文, 胡雨露, 等. 虹膜图像的质量评价研究[J]. 液晶与显示, 2016,31(12):1131-1136. DOI： 10.3788/YJYXS20163112.1131.

Chun-lei SHI, Feng-wen ZHOU, Yu-lu HU, et al. Study for iris image quality assessment[J]. Chinese journal of liquid crystals and displays, 2016, 31(12): 1131-1136. DOI： 10.3788/YJYXS20163112.1131.

摘要

对虹膜识别系统来说，所采集虹膜图像的质量好坏直接影响识别是否成功。本文针对散焦模糊和眼睑睫毛遮挡问题提出了一种新的虹膜图像质量评价方法：判断图像是否散焦模糊采用了LoG算子提取瞳孔两侧局部虹膜的高频能量，判断虹膜是否有眼睑严重遮挡采用了计算瞳孔上方指定矩形区域的灰度均值，同时计算该区域的水平梯度来衡量虹膜受睫毛遮挡的程度。仿真实验表明，算法的平均处理速度0.020 9 s/帧，满足实时虹膜识别系统的需求，是一种快速有效的虹膜图像质量评价算法。

Abstract

The quality of collecting iris image is vital to whether recognizing iris image is right in iris recognition system. A new algorithm is proposed for the defocused and occluded iris images. Firstly the high frequency power of the right and left part of the pupil is calculated by Laplacian of Gaussian operator to discard the defocused images. Secondly

the average gray value of the upper region of the pupil is computed to discard the occluded images by eyelid. Finally

the occluded degree by eyelash is measured through the gradient information of the upper region of the pupil. The experimental results show that

the average processing speed of the algorithm is 0.020 9 s per frame

which fully meets the requirement of real-time iris recognition system

and also shows this algorithm is fast and efficient for iris image quality evaluation.

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Keywords

references

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