Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23781
Title: Unified framework for automated iris segmentation using distantly acquired face images
Authors: Tan, CW
Kumar, A 
Keywords: Biometrics
iris recognition
iris segmentation
unconstrained iris recognition
Issue Date: 2012
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on image processing, 2012, v. 21, no. 9, 6199979, p. 4068-4079 How to cite?
Journal: IEEE transactions on image processing 
Abstract: Remote human identification using iris biometrics has high civilian and surveillance applications and its success requires the development of robust segmentation algorithm to automatically extract the iris region. This paper presents a new iris segmentation framework which can robustly segment the iris images acquired using near infrared or visible illumination. The proposed approach exploits multiple higher order local pixel dependencies to robustly classify the eye region pixels into iris or noniris regions. Face and eye detection modules have been incorporated in the unified framework to automatically provide the localized eye region from facial image for iris segmentation. We develop robust postprocessing operations algorithm to effectively mitigate the noisy pixels caused by the misclassification. Experimental results presented in this paper suggest significant improvement in the average segmentation errors over the previously proposed approaches, i.e., 47.5%, 34.1%, and 32.6% on UBIRIS.v2, FRGC, and CASIA.v4 at-a-distance databases, respectively. The usefulness of the proposed approach is also ascertained from recognition experiments on three different publicly available databases.
URI: http://hdl.handle.net/10397/23781
ISSN: 1057-7149
EISSN: 1941-0042
DOI: 10.1109/TIP.2012.2199125
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