Learning-based license plate detection in vehicle image database

Zhang, H; Jia, W; He, X; Wu, Q

Learning-based license plate detection in vehicle image database

Zhang, H Jia, W

He, X

Wu, Q

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Publication Type:: Journal Article
Citation:: International Journal of Intelligent Information and Database Systems, 2007, 1 (2), pp. 228 - 243
Issue Date:: 2007-01-01

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Field	Value	Language
dc.contributor.author	Zhang, H	en_US
dc.contributor.author	Jia, W https://orcid.org/0000-0002-0940-3338	en_US
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.date.issued	2007-01-01	en_US
dc.identifier.citation	International Journal of Intelligent Information and Database Systems, 2007, 1 (2), pp. 228 - 243	en_US
dc.identifier.issn	1751-5858	en_US
dc.identifier.uri	http://hdl.handle.net/10453/3971
dc.description.abstract	This paper proposes a learning-based algorithm to detect license plates of vehicles from vehicle image database. There are three main contributions in this paper. The first contribution is to define a novel vertical edge map, which makes the image processing more effectively. The second contribution is to propose a learning-based cascade classifier composing of two kinds of sub-classifiers, which makes the system very robust. The third contribution is to experimentally estimate the parameter of scaling factor and chose an optimal one for the algorithm to seek a good balance between detection rate and processing time. © 2007 Inderscience Enterprises Ltd.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0451666
dc.relation.ispartof	International Journal of Intelligent Information and Database Systems	en_US
dc.relation.isbasedon	10.1504/IJIIDS.2007.014952	en_US
dc.title	Learning-based license plate detection in vehicle image database	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	1	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0804 Data Format	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/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	1	en_US

Abstract:

This paper proposes a learning-based algorithm to detect license plates of vehicles from vehicle image database. There are three main contributions in this paper. The first contribution is to define a novel vertical edge map, which makes the image processing more effectively. The second contribution is to propose a learning-based cascade classifier composing of two kinds of sub-classifiers, which makes the system very robust. The third contribution is to experimentally estimate the parameter of scaling factor and chose an optimal one for the algorithm to seek a good balance between detection rate and processing time. © 2007 Inderscience Enterprises Ltd.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/3971