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dc.contributor.authorPal, Srikanta
dc.contributor.authorAlaei, Alireza
dc.contributor.authorPal, Umapada
dc.contributor.authorBlumenstein, Michael
dc.contributor.editorAmir Hussain
dc.date.accessioned2018-10-12T03:52:05Z
dc.date.available2018-10-12T03:52:05Z
dc.date.issued2015
dc.identifier.doi10.1109/IJCNN.2015.7280518
dc.identifier.urihttp://hdl.handle.net/10072/125375
dc.description.abstractThe objective of this investigation is to present an interval-symbolic representation based method for offline signature verification. In the feature extraction stage, Connected Components (CC), Enclosed Regions (ER), Basic Features (BF) and Curvelet Feature (CF)-based approaches are used to characterize signatures. Considering the extracted feature vectors, an interval data value is created for each feature extracted from every individual's signatures as an interval-valued symbolic data. This process results in a signature model for each individual that consists of a set of interval values. A similarity measure is proposed as the classifier in this paper. The interval-valued symbolic representation based method has never been used for signature verification considering Indian script signatures. Therefore, to evaluate the proposed method, a Hindi signature database consisting of 2400 (100×24) genuine signatures and 3000 (100×30) skilled forgeries is employed for experimentation. Concerning this large Hindi signature dataset, the highest verification accuracy of 91.83% was obtained on a joint feature set considering all four sets of features, while 2.5%, 13.84% and 8.17% of FAR (False Acceptance Rate), FRR (False Rejection Rate), and AER (Average Error Rate) were achieved, respectively.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.publisher.placeUnited States
dc.relation.ispartofconferencenameIJCNN 2015
dc.relation.ispartofconferencetitle2015 International Joint Conference on Neural Networks (IJCNN)
dc.relation.ispartofdatefrom2015-07-12
dc.relation.ispartofdateto2015-07-17
dc.relation.ispartoflocationKillarney, Ireland
dc.subject.fieldofresearchArtificial Intelligence and Image Processing not elsewhere classified
dc.subject.fieldofresearchcode080199
dc.titleInterval-valued Symbolic Representation based Method for Off-line Signature Verification
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
dc.description.versionAccepted Manuscript (AM)
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
gro.hasfulltextFull Text
gro.griffith.authorBlumenstein, Michael M.
gro.griffith.authorPal, Srikanta


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