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dc.contributor.authorNguyen, Vuen_US
dc.contributor.authorBlumenstein, Michaelen_US
dc.contributor.editorKaizhu Huang, Di Wenen_US
dc.date.accessioned2017-05-03T15:01:30Z
dc.date.available2017-05-03T15:01:30Z
dc.date.issued2011en_US
dc.date.modified2012-02-08T01:47:57Z
dc.identifier.refurihttp://www.icdar2011.org/EN/volumn/home.shtmlen_US
dc.identifier.urihttp://hdl.handle.net/10072/42407
dc.description.abstractAbstract-Similar to many other pattern recognition problems, feature extraction contributes significantly to the overall performance of an off-line signature verification system. To be successful, a feature extraction technique must be tolerant to different types of variation whilst preserving essential information of input patterns. In this paper, we describe a grid-based feature extraction technique that utilises directional information extracted from the signature contour, i.e. the chain code histogram. Our experimental results for signature verification indicated that, by applying a suitable 2D Gaussian filter on the matrices containing the chain code histograms, an average error rate (AER) of 13.90% can be obtained whilst maintaining the false acceptance rate (FAR) for random forgeries as low as 0.02%. These figures are comparable or better than those reported by other state of the art feature extraction techniques such as the Modified Direction Feature (MDF) and the Gradient feature.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.languageEnglishen_US
dc.publisherIEEEen_US
dc.publisher.placeUnited Statesen_US
dc.publisher.urihttp://www.icdar2011.org/EN/volumn/home.shtmlen_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofconferencenameICDAR 2011en_US
dc.relation.ispartofconferencetitleProceedings of the 11th International Conference on Document Analysis and Recognition (ICDAR 2011)en_US
dc.relation.ispartofdatefrom2011-09-18en_US
dc.relation.ispartofdateto2011-09-21en_US
dc.relation.ispartoflocationBeijing, Chinaen_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchImage Processingen_US
dc.subject.fieldofresearchArtificial Intelligence and Image Processing not elsewhere classifieden_US
dc.subject.fieldofresearchPattern Recognition and Data Miningen_US
dc.subject.fieldofresearchcode080106en_US
dc.subject.fieldofresearchcode080199en_US
dc.subject.fieldofresearchcode080109en_US
dc.titleAn Application of the 2D Gaussian Filter for Enhancing Feature Extraction in Off-line Signature Verificationen_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.date.issued2011
gro.hasfulltextNo Full Text


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

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