Title: A comprehensive approach for sclera image quality measure

Authors: Zhi Zhou; Eliza Y. Du; N. Luke Thomas; Edward J. Delp

Addresses: Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46214, USA ' Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46214, USA ' Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46214, USA ' School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA

Abstract: Poor quality images can affect sclera recognition accuracy. An image quality measure can help improve the recognition system performance. In this paper, we proposed a comprehensive approach for sclera image quality measure, which includes quality filter and quantitative quality assessment unit, segmentation evaluation unit, feature evaluation unit, and score fusion unit. The experimental results show that the combination score is highly correlated with the sclera recognition accuracy and can be used to improve and predict the performance of sclera recognition systems.

Keywords: sclera quality measures; sclera recognition; feature information; segmentation evaluation; score fusion; image quality; biometric recognition; biometrics; blood vessels; white of the eye.

DOI: 10.1504/IJBM.2013.052972

International Journal of Biometrics, 2013 Vol.5 No.2, pp.181 - 198

Received: 20 Jun 2012
Accepted: 29 Aug 2012
Published online: 28 Feb 2014 *

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