Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10693
Title: Automated segmentation of iris images using visible wavelength face images
Authors: Tan, CW
Kumar, A 
Keywords: Face recognition
Image segmentation
Iris recognition
Wavelet transforms
Issue Date: 2011
Publisher: IEEE
Source: 2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 20-25 June 2011, Colorado Springs, CO, p. 9-14 How to cite?
Abstract: Remote human identification using iris biometrics requires the development of automated algorithm of the robust segmentation of iris region pixels from visible face images. This paper presents a new automated iris segmentation framework for iris images acquired at-a-distance using visible imaging. The proposed approach achieves the segmentation of iris region pixels in two stages, i.e. (i) iris and sclera classification, and (ii) post-classification processing. Unlike the traditional edge-based segmentation approaches, the proposed approach simultaneously exploits the discriminative color features and localized Zernike moments to perform pixel-based classification. Rigorous experimental results presented in this paper confirm the usefulness of the proposed approach and achieve improvement of 42.4% in the average segmentation errors, on UBIRIS.v2 dataset, as compared to the previous approach.
URI: http://hdl.handle.net/10397/10693
ISBN: 978-1-4577-0529-8
ISSN: 2160-7508
DOI: 10.1109/CVPRW.2011.5981682
Appears in Collections:Conference Paper

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