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dc.contributor.authorNguyen, Vu
dc.contributor.authorBlumenstein, Michael
dc.contributor.editorKaizhu Huang, Di Wen
dc.date.accessioned2017-05-03T15:01:30Z
dc.date.available2017-05-03T15:01:30Z
dc.date.issued2011
dc.date.modified2012-02-08T01:47:57Z
dc.identifier.refurihttp://www.icdar2011.org/EN/volumn/home.shtml
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.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.publisherIEEE
dc.publisher.placeUnited States
dc.publisher.urihttp://www.icdar2011.org/EN/volumn/home.shtml
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencenameICDAR 2011
dc.relation.ispartofconferencetitleProceedings of the 11th International Conference on Document Analysis and Recognition (ICDAR 2011)
dc.relation.ispartofdatefrom2011-09-18
dc.relation.ispartofdateto2011-09-21
dc.relation.ispartoflocationBeijing, China
dc.rights.retentionY
dc.subject.fieldofresearchImage processing
dc.subject.fieldofresearchArtificial intelligence not elsewhere classified
dc.subject.fieldofresearchcode460306
dc.subject.fieldofresearchcode460299
dc.titleAn Application of the 2D Gaussian Filter for Enhancing Feature Extraction in Off-line Signature Verification
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.date.issued2011
gro.hasfulltextNo Full Text
gro.griffith.authorBlumenstein, Michael M.
gro.griffith.authorNguyen, Vu


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

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