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dc.contributor.convenorK. Rajanikanth
dc.contributor.authorPal, Srikanta
dc.contributor.authorPal, Umapada
dc.contributor.authorBlumenstein, Michael
dc.contributor.editorKumar M., Aswatha; R., Selvarani; Kumar, T V Suresh
dc.date.accessioned2017-05-03T15:48:10Z
dc.date.available2017-05-03T15:48:10Z
dc.date.issued2012
dc.date.modified2013-03-21T00:18:47Z
dc.identifier.refurihttp://icadc.msrit.edu/
dc.identifier.doi10.1007/978-81-322-0740-5_109
dc.identifier.urihttp://hdl.handle.net/10072/49656
dc.description.abstractBiometric systems play a significant role in the field of information security as they are extremely required for user authentication. Signature identification and verification have a great importance for authentication intention. The purpose of this paper is to present an empirical contribution towards the understanding of multi-script (Hindi and English) signature verification. This system will identify whether a claimed signature belongs to the group of English signatures or Hindi signatures from a combined Hindi and English signature datasets and then it will verify signatures using these two resultant signature datasets (Hindi script signature and English script signatures) separately. The modified gradient feature and SVM classifier were employed for identification and verification purposes. To the best of authors' knowledge, the multi-script signature identification and verification has never been used for the task of signature verification and this is the first report of using Hindi and English signatures in this area. Two different results for identification and verification are calculated and analysed. The accuracy of 98.05% is obtained for the identification of signature script using 2160 (1080 Hindi + 1080 English) samples for training and 1080 (540 Hindi + 540 English) samples for testing. The resultant data sets obtained in script identification of signatures were used for verification purpose. The FRR, FAR for Hindi and English was obtained 8.0%, 4.0% and 12.0%, 10.0% respectively.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent173952 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.publisherSpringer
dc.publisher.placeUnited Kingdom
dc.publisher.urihttp://icadc.msrit.edu/
dc.relation.ispartofstudentpublicationY
dc.relation.ispartofconferencenameInternational Conference on Advances in Computing (ICAdC 2012)
dc.relation.ispartofconferencetitleProceedings of International Conference on Advances in Computing
dc.relation.ispartofdatefrom2012-07-04
dc.relation.ispartofdateto2012-07-06
dc.relation.ispartoflocationBangalore, India
dc.rights.retentionY
dc.subject.fieldofresearchImage Processing
dc.subject.fieldofresearchcode080106
dc.titleHindi and English Off-line Signature Identification and Verification
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© 2012 Springer Berlin/India. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher.The original publication is available at www.springerlink.com
gro.date.issued2012
gro.hasfulltextFull Text
gro.griffith.authorBlumenstein, Michael M.
gro.griffith.authorPal, Srikanta


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

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