An application of the 2D Gaussian filter for enhancing feature extraction in off-line signature verification

Nguyen, V; Blumenstein, M

An application of the 2D Gaussian filter for enhancing feature extraction in off-line signature verification

Nguyen, V Blumenstein, M

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, 2011, pp. 339 - 343
Issue Date:: 2011-12-02

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Field	Value	Language
dc.contributor.author	Nguyen, V	en_US
dc.contributor.author	Blumenstein, M https://orcid.org/0000-0002-9908-3744	en_US
dc.date.issued	2011-12-02	en_US
dc.identifier.citation	Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, 2011, pp. 339 - 343	en_US
dc.identifier.isbn	9780769545202	en_US
dc.identifier.issn	1520-5363	en_US
dc.identifier.uri	http://hdl.handle.net/10453/119475
dc.description.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. © 2011 IEEE.	en_US
dc.relation.ispartof	Proceedings of the International Conference on Document Analysis and Recognition, ICDAR	en_US
dc.relation.isbasedon	10.1109/ICDAR.2011.76	en_US
dc.title	An application of the 2D Gaussian filter for enhancing feature extraction in off-line signature verification	en_US
dc.type	Conference Proceeding
utslib.for	0803 Computer Software	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Strength - QSI - Centre for Quantum Software and Information
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

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. © 2011 IEEE.

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http://hdl.handle.net/10453/119475