Show simple item record

dc.contributor.authorZhao, S
dc.contributor.authorGao, Y
dc.contributor.authorCaelli, T
dc.contributor.editorIAPR
dc.date.accessioned2017-05-03T15:01:08Z
dc.date.available2017-05-03T15:01:08Z
dc.date.issued2010
dc.date.modified2011-04-18T06:57:11Z
dc.identifier.isbn9780769541099
dc.identifier.issn1051-4651
dc.identifier.refurihttp://www.icpr2010.org/
dc.identifier.doi10.1109/ICPR.2010.550
dc.identifier.urihttp://hdl.handle.net/10072/36156
dc.description.abstractMicropattern based image representation and recognition, e.g. Local Binary Pattern (LBP), has been proved successful over the past few years due to its advantages of illumination tolerance and computational efficiency. However, LBP only encodes the first-order radial-directional derivatives of spatial images and is inadequate to completely describe the discriminative features for classification. This paper proposes a new Circular Derivative Pattern (CDP) which extracts high-order derivative information of images along circular directions. We argue that the high-order circular derivatives contain more detailed and more discriminative information than the first-order LBP in terms of recognition accuracy. Experimental evaluation through face recognition on the FERET database and insect classification on the NICTA Biosecurity Dataset demonstrated the effectiveness of the proposed method.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent617121 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.ispartofpagefrom2246
dc.relation.ispartofpageto2249
dc.rights.retentionY
dc.subject.fieldofresearchComputer vision
dc.subject.fieldofresearchcode460304
dc.titleHigh-Order Circular Derivative Pattern for Image Representation and 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
gro.griffith.authorZhao, Sanqiang


Files in this item

This item appears in the following Collection(s)

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

Show simple item record