Iris image segmentation and sub-optimal images

被引：17

作者：

Matey, James R. ^{[1
]}

Broussard, Randy ^{[1
]}

Kennell, Lauren ^{[2
]}

机构：

[1] USN Acad, Ctr Biometr Signal Proc, ECE Dept, Annapolis, MD 21402 USA

[2] Johns Hopkins Appl Phys Lab, Laurel, MD 20723 USA

来源：

IMAGE AND VISION COMPUTING | 2010年 / 28卷 / 02期

关键词：

Biometric; Iris recognition; Iris segmentation; RECOGNITION;

D O I：

10.1016/j.imavis.2009.05.006

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Iris recognition is well developed and works well for optimal or near-optimal iris images. Dealing with sub-optimal images remains a challenge. Resolution, wavelength, occlusion and gaze are among the most important factors for sub-optimal images. In this paper, we explore the sensitivity of matching to these factors through analysis and numerical simulation, with particular emphasis on the segmentation portion of the processing chain. (C) 2009 Published by Elsevier B.V.

引用

页码：215 / 222

页数：8

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