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dc.contributor.convenorJosep Lladósen_AU
dc.contributor.authorNguyen, Vuen_US
dc.contributor.authorBlumenstein, Michaelen_US
dc.contributor.authorLeedham, Grahamen_US
dc.contributor.editorBob Werneren_US
dc.date.accessioned2017-05-03T13:03:27Z
dc.date.available2017-05-03T13:03:27Z
dc.date.issued2009en_US
dc.date.modified2010-06-03T09:03:08Z
dc.identifier.refurihttp://www.icdar2009.orgen_AU
dc.identifier.doi10.1109/ICDAR.2009.123en_AU
dc.identifier.urihttp://hdl.handle.net/10072/29990
dc.description.abstractGlobal features based on the boundary of a signature and its projections are described for enhancing the process of automated signature verification. The first global feature is derived from the total 'energy' a writer uses to create their signature. The second feature employs information from the vertical and horizontal projections of a signature, focusing on the proportion of the distance between key strokes in the image, and the height/width of the signature. The combination of these features with the Modified Direction Feature (MDF) and the ratio feature showed promising results for the off-line signature verification problem. When being trained using 12 genuine specimens and 400 random forgeries taken from a publicly available database, the Support Vector Machine (SVM) classifier obtained an average error rate (AER) of 17.25%. The false acceptance rate (FAR) for random forgeries was also kept as low as 0.08%.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent804812 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherIEEE Computer Societyen_US
dc.publisher.placeLos Alamitos, CAen_US
dc.relation.ispartofstudentpublicationYen_AU
dc.relation.ispartofconferencename10th International Conference on Document Analysis and Recognitionen_US
dc.relation.ispartofconferencetitleProceedings of the 10th International Conference on Document Analysis annd Recognitionen_US
dc.relation.ispartofdatefrom2009-07-26en_US
dc.relation.ispartofdateto2009-07-29en_US
dc.relation.ispartoflocationBarcelonaen_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchPattern Recognition and Data Miningen_US
dc.subject.fieldofresearchNeural, Evolutionary and Fuzzy Computationen_US
dc.subject.fieldofresearchcode080109en_US
dc.subject.fieldofresearchcode080108en_US
dc.titleGlobal Features for the Off-Line Signature Verification Problemen_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 2009 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.issued2009
gro.hasfulltextFull Text


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