On shape-mediated enrolment in ear biometrics

Authors: Arbab-Zavar, B. and Nixon, M.S.

Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume: 4842 LNCS

Issue: PART 2

Pages: 549-558

eISSN: 1611-3349

ISBN: 9783540768555

ISSN: 0302-9743

DOI: 10.1007/978-3-540-76856-2_54


Ears are a new biometric with major advantage in that they appear to maintain their shape with increased age. Any automatic biometric system needs enrolment to extract the target area from the background. In ear biometrics the inputs are often human head profile images. Furthermore ear biometrics is concerned with the effects of partial occlusion mostly caused by hair and earrings. We propose an ear enrolment algorithm based on finding the elliptical shape of the ear using a Hough Transform (HT) accruing tolerance to noise and occlusion. Robustness is improved further by enforcing some prior knowledge. We assess our enrolment on two face profile datasets; as well as synthetic occlusion. © Springer-Verlag Berlin Heidelberg 2007.

Source: Scopus