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dc.contributor.authorKanan, Hamidreza Rashidy
dc.contributor.authorFaez, Karim
dc.contributor.authorGao, Yongsheng
dc.contributor.editorDr. Robert S Ledley (Editor-in-Chief), C Y Suen (Editor-in-Chief)
dc.date.accessioned2017-05-03T14:13:03Z
dc.date.available2017-05-03T14:13:03Z
dc.date.issued2008
dc.date.modified2011-06-30T08:43:12Z
dc.identifier.issn0031-3203
dc.identifier.doi10.1016/j.patcog.2008.05.024
dc.identifier.urihttp://hdl.handle.net/10072/23685
dc.description.abstractThough 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
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherPergamon/Elsevier
dc.publisher.placeUnited Kingdom
dc.relation.ispartofstudentpublicationY
dc.relation.ispartofpagefrom3799
dc.relation.ispartofpageto3812
dc.relation.ispartofissue12
dc.relation.ispartofjournalPattern Recognition
dc.relation.ispartofvolume41
dc.rights.retentionY
dc.subject.fieldofresearchInformation systems
dc.subject.fieldofresearchcode4609
dc.titleFace recognition using adaptively weighted patch PZM array from a single exemplar image per person
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.date.issued2008
gro.hasfulltextNo Full Text
gro.griffith.authorGao, Yongsheng


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