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dc.contributor.convenorAndy Downton and Mike Fairhursten_AU
dc.contributor.authorBlumenstein, Michaelen_US
dc.contributor.authorVerma, Brijeshen_US
dc.contributor.authorBasli, Hasanen_US
dc.contributor.editorBob Werneren_US
dc.date.accessioned2017-04-24T10:08:50Z
dc.date.available2017-04-24T10:08:50Z
dc.date.issued2003en_US
dc.date.modified2009-09-24T05:54:47Z
dc.identifier.doi10.1109/ICDAR.2003.1227647en_AU
dc.identifier.urihttp://hdl.handle.net/10072/1767
dc.description.abstractHigh accuracy character recognition techniques can provide useful information for segmentation-based handwritten word recognition systems. This research describes neural network-based techniques for segmented character recognition that may be applied to the segmentation and recognition components of an off-line handwritten word recognition system. Two neural architectures along with two different feature extraction techniques were investigated. A novel technique for character feature extraction is discussed and compared with others in the literature. Recognition results above 80% are reported using characters automatically segmented from the CEDAR benchmark database as well as standard CEDAR alphanumerics.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent209954 bytes
dc.format.extent24488 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherIEEE Computer Societyen_US
dc.publisher.placeLos Alamitos, USAen_US
dc.publisher.urihttp://ieeexplore.ieee.org/servlet/opac?punumber=8701en_AU
dc.relation.ispartofconferencenameInternational Conference on Document Analysis and Recognition (ICDAR 2003)en_US
dc.relation.ispartofconferencetitleProceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR '03)en_US
dc.relation.ispartofdatefrom2003-08-03en_US
dc.relation.ispartofdateto2003-08-06en_US
dc.relation.ispartoflocationEdinburgh, Scotlanden_US
dc.subject.fieldofresearchcode280207en_US
dc.titleA Novel Feature Extraction Technique for the Recognition of Segmented Handwritten Charactersen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.facultyGriffith Sciences, School of Information and Communication Technologyen_US
gro.rights.copyrightCopyright 2003 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.en_AU
gro.date.issued2003
gro.hasfulltextFull Text


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

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