Face recognition using adaptively weighted patch PZM array from a single exemplar image per person

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Title Face recognition using adaptively weighted patch PZM array from a single exemplar image per person
Author Kanan, Hamidreza Rashidy; Faez, Karim; Gao, Yongsheng
Journal Name Pattern Recognition
Editor Dr. Robert S Ledley (Editor-in-Chief), C Y Suen (Editor-in-Chief)
Year Published 2008
Place of publication United Kingdom
Publisher Pergamon/Elsevier
Abstract Though numerous approaches have been proposed for face recognition, little attention is given to the moment-based face recognition techniques. In this paper we propose a novel face recognition approach based on adaptively weighted patch pseudo Zernike moment array (AWPPZMA) when only one exemplar image per person is available. In this approach, a face image is represented as an array of patch pseudo Zernike moments (PPZM) extracted from a partitioned face image containing moment information of local areas instead of global information of a face. An adaptively weighting scheme is used to assign proper weights to each PPZM to adjust the contribution of each local area of a face in terms of the quantity of identity information that a patch contains and the likelihood of a patch is occluded. An extensive experimental investigation is conducted using AR and Yale face databases covering face recognition under controlled/ideal conditions, different illumination conditions, different facial expressions and partial occlusion. The system performance is compared with the performance of four benchmark approaches. The encouraging experimental results demonstrate that moments can be used for face recognition and patch-based moment array provides a novel way for face representation and recognition in single model databases. Keywords: Face recognition; Adaptively weighted patch pseudo Zernike moment; Zernike moment; Patch matching; Local matching; Partial occlusion; Single model database
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1016/j.patcog.2008.05.024
Volume 41
Issue Number 12
Page from 3799
Page to 3812
ISSN 0031-3203
Date Accessioned 2008-09-18
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject PRE2009-Computer Vision; PRE2009-Pattern Recognition
URI http://hdl.handle.net/10072/23685
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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