Experiments with an improved iris segmentation algorithm

被引：0
|
作者：
Liu, XM [1 ]
Bowyer, KW [1 ]
Flynn, PJ [1 ]
机构：
[1] Univ Notre Dame, Dept Comp Sci & Engn, Notre Dame, IN 46556 USA
来源：
FOURTH IEEE WORKSHOP ON AUTOMATIC IDENTIFICATION ADVANCED TECHNOLOGIES, PROCEEDINGS | 2005年
关键词：
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：
Iris is claimed to be one of the best biometrics. We have collected a large data set of iris images, intentionally sampling a range of quality broader than that used by current commercial iris recognition systems. We have re-implemented the Daugman-like iris recognition algorithm developed by Masek Me have also developed and implemented an improved iris segmentation and eyelid detection stage of the algorithm, and experimentally veri ed the improvement in recognition performance using the collected dataset. Compared to Masek's original segmentation approach, our improved segmentation algorithm leads to an increase of over 6% in the rank-one recognition rate.
引用
收藏
页码：118 / 123
页数：6
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