Iris recognition:: A method to increase the robustness to noisy Imaging environments through the selection of the higher discriminating features

被引:1
作者
Proenca, Hugo [1 ]
Alexandre, Luis A. [1 ]
机构
[1] Univ Beira Interior, Dept Comp Sci, IT Networks & Multimedia Grp, Covilha, Portugal
来源
ICCIMA 2007: INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND MULTIMEDIA APPLICATIONS, VOL III, PROCEEDINGS | 2007年
关键词
iris recognition; feature selection; biometrics;
D O I
10.1109/ICCIMA.2007.119
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Continuous efforts have been made in searching for robust and effective iris coding methods, since Daugman's pioneering work on it-is recognition was published. However, due to lack of robustness, the error rates of iris recognition systems significantly increase when images contain large portions of noise (reflections and it-is obstructions), resultant from less constrained imaging conditions. Current iris encoding and matching proposals do not take into account the specific lighting conditions of the imaging environment, decreasing their adaptability to such dynamics conditions. In this paper we propose a method that, through a learning stage, takes into account the typical noisy regions propitiated by the imaging environment to select the higher discriminating features. Our experiments were performed on two well known iris image databases (CASIA and UBIRIS) and show a significant decrease of the error rates in the recognition of iris images corrupted by noise.
引用
收藏
页码:301 / 307
页数:7
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