Title: Iris recognition based on robust iris segmentation and image enhancement

Authors: Abhishek Verma; Chengjun Liu; Jiancheng (Kevin) Jia

Addresses: Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA. ' Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA. ' Department of Test Engineering, International Game Technology, Reno, NV 89521, USA

Abstract: A new iris recognition method based on a robust iris segmentation approach is presented in this paper for improving iris recognition performance. The robust iris segmentation approach applies power-law transformations for more accurate detection of the pupil region, which significantly reduces the candidate limbic boundary search space for increasing detection accuracy and efficiency. The limbic circle having a centre within close range of the pupil centre is selectively detected, and the eyelid detection approach thus leads to improved iris recognition performance. Experiments using the Iris Challenge Evaluation (ICE) database show the effectiveness of the proposed method.

Keywords: iris recognition; iris segmentation; power-law transformations; ICE; iris challenge evaluation; biometrics; eyelid detection.

DOI: 10.1504/IJBM.2012.044295

International Journal of Biometrics, 2012 Vol.4 No.1, pp.56 - 76

Received: 04 Mar 2011
Accepted: 11 Apr 2011
Published online: 29 Nov 2014 *

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