dc.contributor.convenor | Josep Lladós | |
dc.contributor.author | Nguyen, Vu | |
dc.contributor.author | Blumenstein, Michael | |
dc.contributor.author | Leedham, Graham | |
dc.contributor.editor | Bob Werner | |
dc.date.accessioned | 2017-05-03T13:03:27Z | |
dc.date.available | 2017-05-03T13:03:27Z | |
dc.date.issued | 2009 | |
dc.date.modified | 2010-06-03T09:03:08Z | |
dc.identifier.refuri | http://www.icdar2009.org | |
dc.identifier.doi | 10.1109/ICDAR.2009.123 | |
dc.identifier.uri | http://hdl.handle.net/10072/29990 | |
dc.description.abstract | Global 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%. | |
dc.description.peerreviewed | Yes | |
dc.description.publicationstatus | Yes | |
dc.format.extent | 804812 bytes | |
dc.format.mimetype | application/pdf | |
dc.language | English | |
dc.language.iso | eng | |
dc.publisher | IEEE Computer Society | |
dc.publisher.place | Los Alamitos, CA | |
dc.relation.ispartofstudentpublication | Y | |
dc.relation.ispartofconferencename | 10th International Conference on Document Analysis and Recognition | |
dc.relation.ispartofconferencetitle | Proceedings of the 10th International Conference on Document Analysis annd Recognition | |
dc.relation.ispartofdatefrom | 2009-07-26 | |
dc.relation.ispartofdateto | 2009-07-29 | |
dc.relation.ispartoflocation | Barcelona | |
dc.rights.retention | Y | |
dc.subject.fieldofresearch | Pattern Recognition and Data Mining | |
dc.subject.fieldofresearch | Neural, Evolutionary and Fuzzy Computation | |
dc.subject.fieldofresearchcode | 080109 | |
dc.subject.fieldofresearchcode | 080108 | |
dc.title | Global Features for the Off-Line Signature Verification Problem | |
dc.type | Conference output | |
dc.type.description | E1 - Conferences | |
dc.type.code | E - Conference Publications | |
gro.faculty | Griffith Sciences, School of Information and Communication Technology | |
gro.rights.copyright | © 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. | |
gro.date.issued | 2009 | |
gro.hasfulltext | Full Text | |
gro.griffith.author | Blumenstein, Michael M. | |
gro.griffith.author | Nguyen, Vu | |