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dc.contributor.authorZhao, S
dc.contributor.authorGao, Y
dc.contributor.authorZhang, B
dc.contributor.editorIAPR
dc.date.accessioned2017-05-03T15:01:18Z
dc.date.available2017-05-03T15:01:18Z
dc.date.issued2010
dc.date.modified2011-04-18T06:54:32Z
dc.identifier.isbn9780769541099
dc.identifier.issn1051-4651
dc.identifier.refurihttp://www.icpr2010.org/
dc.identifier.doi10.1109/ICPR.2010.317
dc.identifier.urihttp://hdl.handle.net/10072/36141
dc.description.abstractFace recognition using micropattern representation has recently received much attention in the computer vision and pattern recognition community. Previous researches demonstrated that micropattern representation based on Gabor features achieves better performance than its direct usage on gray-level images. This paper conducts a comparative performance evaluation of micropattern representations on four forms of Gabor features for face recognition. Three evaluation rules are proposed and observed for a fair comparison. To reduce the high feature dimensionality problem, uniform quantization is used to partition the spatial histograms. The experimental results reveal that: 1) micropattern representation based on Gabor magnitude features outperforms the other three representations, and the performances of the other three are comparable; and 2) micropattern representation based on the combination of Gabor magnitude and phase features performs the best.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent556939 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherIEEE Computer Society
dc.publisher.placeUnited States
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencenameThe 20th International Conference on Pattern Recognition (ICPR 2010)
dc.relation.ispartofconferencetitleProceedings - International Conference on Pattern Recognition
dc.relation.ispartofdatefrom2010-08-23
dc.relation.ispartofdateto2010-08-26
dc.relation.ispartoflocationIstanbul, Turkey
dc.relation.ispartofpagefrom1273
dc.relation.ispartofpageto1276
dc.rights.retentionY
dc.subject.fieldofresearchComputer vision
dc.subject.fieldofresearchcode460304
dc.titlePerformance Evaluation of Micropattern Representation on Gabor Features for Face Recognition
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, Griffith School of Engineering
gro.rights.copyright© 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
gro.date.issued2010
gro.hasfulltextFull Text
gro.griffith.authorGao, Yongsheng


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    Contains papers delivered by Griffith authors at national and international conferences.

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