Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/19284
Title: Towards online iris and periocular recognition under relaxed imaging constraints
Authors: Tan, CW
Kumar, A 
Keywords: Identification at-a-distance
Iris recognition
Iris segmentation
Periocular recognition
Remote biometrics
Issue Date: 2013
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on image processing, 2013, v. 22, no. 10, 6508951, p. 3751-3765 How to cite?
Journal: IEEE transactions on image processing 
Abstract: Online iris recognition using distantly acquired images in a less imaging constrained environment requires the development of a efficient iris segmentation approach and recognition strategy that can exploit multiple features available for the potential identification. This paper presents an effective solution toward addressing such a problem. The developed iris segmentation approach exploits a random walker algorithm to efficiently estimate coarsely segmented iris images. These coarsely segmented iris images are postprocessed using a sequence of operations that can effectively improve the segmentation accuracy. The robustness of the proposed iris segmentation approach is ascertained by providing comparison with other state-of-the-art algorithms using publicly available UBIRIS.v2, FRGC, and CASIA.v4-distance databases. Our experimental results achieve improvement of 9.5%, 4.3%, and 25.7% in the average segmentation accuracy, respectively, for the UBIRIS.v2, FRGC, and CASIA.v4-distance databases, as compared with most competing approaches. We also exploit the simultaneously extracted periocular features to achieve significant performance improvement. The joint segmentation and combination strategy suggest promising results and achieve average improvement of 132.3%, 7.45%, and 17.5% in the recognition performance, respectively, from the UBIRIS.v2, FRGC, and CASIA.v4-distance databases, as compared with the related competing approaches.
URI: http://hdl.handle.net/10397/19284
ISSN: 1057-7149 (print)
1941-0042 (online)
DOI: 10.1109/TIP.2013.2260165
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