Transforming Traditional Iris Recognition Systems to Work in Nonideal Situations
Zhi Zhou
Yingzi Du
Belcher, C.
Electr. & Comput. Eng. Dept., Indiana Univ.-Purdue Univ. Indianapolis, Indianapolis, IN, USA;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: Aug. 2009
Volume: 56,
Issue: 8
On page(s): 3203-3213
ISSN: 0278-0046
INSPEC Accession Number: 10793151
Digital Object Identifier: 10.1109/TIE.2009.2024653
First Published: 2009-06-10
Current Version Published: 2009-07-24
Abstract
Under a nonideal situation, the image quality may vary. As a result, the traditional iris recognition systems would not work well. However, these kinds of iris recognition systems have been widely deployed in law enforcement and homeland security. It will be desirable to transform the traditional systems to perform in nonideal situations without a costly update. In this paper, we propose a method that upgrades the traditional iris recognition system to work on nonideal situations. The proposed method takes into consideration not only the effect of image quality but also the segmentation accuracy. It employs video-based image-processing techniques to quickly identify and eliminate the bad quality images from iris videos for further processing. The proposed method is tested on public databases using in-house recognition algorithms and also evaluated using a commercialized system. The research results show that the proposed methods can be used to improve the performance of iris recognition systems in a nonideal situation.
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