Computer Engineering and Applications ›› 2017, Vol. 53 ›› Issue (15): 196-199.DOI: 10.3778/j.issn.1002-8331.1603-0006

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Iris recognition algorithm based on texture energy features

DENG Yubo, SU Juan   

  1. College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
  • Online:2017-08-01 Published:2017-08-14

基于纹理方向能量特征的虹膜识别算法

邓玉波,苏  娟   

  1. 湖南大学 电气与信息工程学院,长沙 410082

Abstract: In order to solve the problem that the traditional iris recognition system’s performance isn’t good enough under non-ideal image conditions, a novel algorithm based on texture energy features is proposed. Firstly, a set of horizontal and vertical direction filter is designed to extract iris texture edge. The characteristic figures exhibiting the differences of direction energy are generated by comparing the energy intensity of iris texture edge in the two directions, horizontal and vertical. Secondly, the figures are divided into different parts, and the maximal point of every energy difference is selected as an effective point to obtain eigenvector. Besides, swelling the noise template and ruling out the influence of noise point and convolution noise point on the surrounding effective figures. Finally, the hamming distance matching vector is obtained to implement iris recognition. The method is tested by CASIA3.0 iris database provided by Chinese Academy of Sciences gaining a good recognition rate.

Key words: iris recognition, feature extraction, directional energy characteristics, rotational and translational invariance

摘要: 为了解决传统虹膜识别系统在非理想虹膜图像下识别性能不够好的问题,提出了基于纹理方向能量特征的虹膜识别方法。该方法先设计一组水平与垂直的方向滤波器提取虹膜的纹理边缘,比较虹膜纹理边缘在两个方向的能量强度,生成方向能量差异特征图。将特征图分块,选取每块能量差值的极值点作为有效特征点,编码生成特征向量。此外,膨胀噪声模板,消除噪声以及卷积运算中噪声点对周围有效特征点的影响。用汉明距离进行匹配。在采用中科院提供的CASIA3.0虹膜库测试中获得了较好的识别率。

关键词: 虹膜识别, 特征提取, 方向能量特征, 旋转平移不变性