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Proceedings Paper

A novel iris segmentation algorithm based on small eigenvalue analysis
Author(s): B. S. Harish; S. V. Aruna Kumar; D. S. Guru; Minh Ngoc Ngo
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Paper Abstract

In this paper, a simple and robust algorithm is proposed for iris segmentation. The proposed method consists of two steps. In first step, iris and pupil is segmented using Robust Spatial Kernel FCM (RSKFCM) algorithm. RSKFCM is based on traditional Fuzzy-c-Means (FCM) algorithm, which incorporates spatial information and uses kernel metric as distance measure. In second step, small eigenvalue transformation is applied to localize iris boundary. The transformation is based on statistical and geometrical properties of the small eigenvalue of the covariance matrix of a set of edge pixels. Extensive experimentations are carried out on standard benchmark iris dataset (viz. CASIA-IrisV4 and UBIRIS.v2). We compared our proposed method with existing iris segmentation methods. Our proposed method has the least time complexity of O(n(i+p)) . The result of the experiments emphasizes that the proposed algorithm outperforms the existing iris segmentation methods.

Paper Details

Date Published: 9 December 2015
PDF: 5 pages
Proc. SPIE 9817, Seventh International Conference on Graphic and Image Processing (ICGIP 2015), 98170M (9 December 2015); doi: 10.1117/12.2228453
Show Author Affiliations
B. S. Harish, Sri Jayachamarajendra College of Engineering (India)
S. V. Aruna Kumar, Sri Jayachamarajendra College of Engineering (India)
D. S. Guru, Univ. of Mysore (India)
Minh Ngoc Ngo, Singapore Institute of Technology (Singapore)

Published in SPIE Proceedings Vol. 9817:
Seventh International Conference on Graphic and Image Processing (ICGIP 2015)
Yulin Wang; Xudong Jiang, Editor(s)

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