A novel approach for curvature detection in global fingerprint feature extraction

Mastali, N

A novel approach for curvature detection in global fingerprint feature extraction

Mastali, N

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Publication Type:: Conference Proceeding
Citation:: 2012 International Conference on Informatics, Electronics and Vision, ICIEV 2012, 2012, pp. 1059 - 1063
Issue Date:: 2012-11-26

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Field	Value	Language
dc.contributor.author	Mastali, N	en_US
dc.date.issued	2012-11-26	en_US
dc.identifier.citation	2012 International Conference on Informatics, Electronics and Vision, ICIEV 2012, 2012, pp. 1059 - 1063	en_US
dc.identifier.isbn	9781467311519	en_US
dc.identifier.uri	http://hdl.handle.net/10453/31740
dc.description.abstract	Fingerprint features extraction plays a critical role on any Automatic Fingerprint Identification System (AFIS). Extracting curvatures from the fingerprint accurately is a critical step in AFIS and optimizing its computation without losing the resolution could be very beneficial as it is for any process in applications consisting of image processing. In curvature extraction progressing in variable steps shows advantages versus the current fixed step methods. Experimental results show the proposed approach could improve the truthfulness of the extracted curves as well as the process time. As anticipated, the difference is more visible in high curvature ridges. © 2012 IEEE.	en_US
dc.relation.ispartof	2012 International Conference on Informatics, Electronics and Vision, ICIEV 2012	en_US
dc.relation.isbasedon	10.1109/ICIEV.2012.6317538	en_US
dc.title	A novel approach for curvature detection in global fingerprint feature extraction	en_US
dc.type	Conference Proceeding
utslib.for	0906 Electrical and Electronic Engineering	en_US
dc.location.activity	Dhaka
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
utslib.copyright.status	closed_access
pubs.declined	2014-11-26T23:16:09.918+1100
pubs.publication-status	Published	en_US

Abstract:

Fingerprint features extraction plays a critical role on any Automatic Fingerprint Identification System (AFIS). Extracting curvatures from the fingerprint accurately is a critical step in AFIS and optimizing its computation without losing the resolution could be very beneficial as it is for any process in applications consisting of image processing. In curvature extraction progressing in variable steps shows advantages versus the current fixed step methods. Experimental results show the proposed approach could improve the truthfulness of the extracted curves as well as the process time. As anticipated, the difference is more visible in high curvature ridges. © 2012 IEEE.

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http://hdl.handle.net/10453/31740