dc.contributor.author | Nguyen, Vu | |
dc.contributor.author | Blumenstein, Michael | |
dc.contributor.editor | Kaizhu Huang, Di Wen | |
dc.date.accessioned | 2017-05-03T15:01:30Z | |
dc.date.available | 2017-05-03T15:01:30Z | |
dc.date.issued | 2011 | |
dc.date.modified | 2012-02-08T01:47:57Z | |
dc.identifier.refuri | http://www.icdar2011.org/EN/volumn/home.shtml | |
dc.identifier.uri | http://hdl.handle.net/10072/42407 | |
dc.description.abstract | Abstract-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.peerreviewed | Yes | |
dc.description.publicationstatus | Yes | |
dc.language | English | |
dc.publisher | IEEE | |
dc.publisher.place | United States | |
dc.publisher.uri | http://www.icdar2011.org/EN/volumn/home.shtml | |
dc.relation.ispartofstudentpublication | N | |
dc.relation.ispartofconferencename | ICDAR 2011 | |
dc.relation.ispartofconferencetitle | Proceedings of the 11th International Conference on Document Analysis and Recognition (ICDAR 2011) | |
dc.relation.ispartofdatefrom | 2011-09-18 | |
dc.relation.ispartofdateto | 2011-09-21 | |
dc.relation.ispartoflocation | Beijing, China | |
dc.rights.retention | Y | |
dc.subject.fieldofresearch | Image processing | |
dc.subject.fieldofresearch | Artificial intelligence not elsewhere classified | |
dc.subject.fieldofresearchcode | 460306 | |
dc.subject.fieldofresearchcode | 460299 | |
dc.title | An Application of the 2D Gaussian Filter for Enhancing Feature Extraction in Off-line Signature Verification | |
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.date.issued | 2011 | |
gro.hasfulltext | No Full Text | |
gro.griffith.author | Blumenstein, Michael M. | |
gro.griffith.author | Nguyen, Vu | |