Robust Sclera Recognition System with Novel Sclera Segmentation and Validation Techniques

S. Alkassar, W. L. Woo, S. S. Dlay, J. A. Chambers

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)

Abstract

Sclera blood veins have been investigated recently as a biometric trait which can be used in a recognition system. The sclera is the white and opaque outer protective part of the eye. This part of the eye has visible blood veins which are randomly distributed. This feature makes these blood veins a promising factor for eye recognition. The sclera has an advantage in that it can be captured using a visible-wavelength camera. Therefore, applications which may involve the sclera are wide ranging. The contribution of this paper is the design of a robust sclera recognition system with high accuracy. The system comprises of new sclera segmentation and occluded eye detection methods. We also propose an efficient method for vessel enhancement, extraction, and binarization. In the feature extraction and matching process stages, we additionally develop an efficient method, that is, orientation, scale, illumination, and deformation invariant. The obtained results using UBIRIS.v1 and UTIRIS databases show an advantage in terms of segmentation accuracy and computational complexity compared with state-of-the-art methods due to Thomas, Oh, Zhou, and Das.
Original languageEnglish
Pages (from-to)474-486
Number of pages13
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume47
Issue number3
Early online date24 Dec 2015
DOIs
Publication statusPublished - Mar 2017

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