EFFECT OF EYELID AND EYELASH OCCLUSIONS ON IRIS IMAGES USING SUBPATTERN-BASED APPROACHES

被引：0
|
作者：
Eskandari, Maryam [1 ]
Toygar, Oensen [1 ]
机构：
[1] Eastern Mediterranean Univ, Dept Comp Engn, Gazimagusa, Cyprus
来源：
2009 FIFTH INTERNATIONAL CONFERENCE ON SOFT COMPUTING, COMPUTING WITH WORDS AND PERCEPTIONS IN SYSTEM ANALYSIS, DECISION AND CONTROL | 2010年
关键词：
Iris recognition; PCA; subpattern-based approaches; occlusion; RECOGNITION; PCA;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The effect of eyelid and eyelash occlusions on iris images is investigated in this study using subpattern-based approaches. Principal Component Analysis (PCA), subpattern-based PCA (spPCA) and modular PCA (mPCA) methods are used as feature extractors to recognize occluded iris images. In order to eliminate the effect of illumination changes, histogram equalization and mean-and-variance normalization techniques are used. Various experiments are carried out on UBIRIS, CASIA and MMU iris databases to demonstrate the effect of eyelid and eyelash occlusions on iris images. The results of the experiments are consistent with the results of other biometrics systems using PCA, spPCA and mPCA approaches.
引用
收藏
页码：117 / 120
页数：4
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