华南理工大学学报(自然科学版) ›› 2009, Vol. 37 ›› Issue (5): 43-48.

• 电子、通信与自动控制 • 上一篇    下一篇

用于身份鉴别的虹膜图像预处理

罗忠亮 林土胜   

  1. 华南理工大学 电子与信息学院, 广东 广州 510640
  • 收稿日期:2008-07-07 修回日期:2008-10-17 出版日期:2009-05-25 发布日期:2009-05-25
  • 通信作者: 罗忠亮(1973-),男,博士生,主要从事数字图像处理与生物特征识别研究. E-mail:luoz166@yahoo.com.cn
  • 作者简介:罗忠亮(1973-),男,博士生,主要从事数字图像处理与生物特征识别研究.
  • 基金资助:

    国家自然科学基金资助项目(60472006);广东省自然科学基金团队研究项目(04205783)

Preprocessing of Iris Image for Identification Recognition

Luo Zhong-liang  Lin Tu-sheng   

  1. School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510640, Guangdong, China
  • Received:2008-07-07 Revised:2008-10-17 Online:2009-05-25 Published:2009-05-25
  • Contact: 罗忠亮(1973-),男,博士生,主要从事数字图像处理与生物特征识别研究. E-mail:luoz166@yahoo.com.cn
  • About author:罗忠亮(1973-),男,博士生,主要从事数字图像处理与生物特征识别研究.
  • Supported by:

    国家自然科学基金资助项目(60472006);广东省自然科学基金团队研究项目(04205783)

摘要: 针对虹膜图像的特点和现有虹膜识别算法运算速度慢及鲁棒性差的问题,为提高虹膜识别的性能,提出了一种新的虹膜图像预处理方法.首先采用最小二乘法定位虹膜内边缘和检测上下眼睑,利用改进的随机Hough变换定位外边缘;然后运用双闲值法检测睫毛,并对分割出的环状虹膜区域进行归一化和去噪与增强处理.预处理后的图像基本上不含眼睑和睫毛等干扰,从而有利于后续的虹膜特征提取和匹配.测试结果表明,该方法可有效地解决图像预处理中计算时间长和通用性差的问题,能提高虹膜识别系统的稳定性和识别率.

关键词: 图像预处理, 虹膜识别, 虹膜定位, 干扰检测

Abstract:

The existing iris recognition algorithms are of low executing speed and poor robustness. In order to im- prove the accuracy of iris recognition, a novel preprocessing approach is proposed according to the characteristics of iris images. In this approach, first, the least square method is used to locate the inner iris boundary and to test the eyelid. Next, the improved randomized Hough transform is adopted to locate the outer iris boundary. Then, the double-threshold method is employed to detect the eyelash. Finally, a normalizing, de-noising and enhancing process is performed for the circular iris image. The iris image after the preprocessing basically eliminates the dis- turbance of eyelid and eyelash, thus facilitating the following extraction and matching of iris features. Experimental results demonstrate that the proposed approach effectively overcomes the long runtime and the poor generality in image preprocessing, and improves the stability and accuracy of iris recognition system.

Key words: image preprocessing, iris recognition, iris localization, disturbance detection