Accuracy enhancement for license plate recognition

Zheng, L; He, X; Samali, B; Yang, LT

Accuracy enhancement for license plate recognition

Zheng, L He, X

Samali, B

Yang, LT

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 10th IEEE International Conference on Computer and Information Technology, CIT-2010, 7th IEEE International Conference on Embedded Software and Systems, ICESS-2010, ScalCom-2010, 2010, pp. 511 - 516
Issue Date:: 2010-11-19

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Field	Value	Language
dc.contributor.author	Zheng, L	en_US
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.contributor.author	Samali, B https://orcid.org/0000-0002-3426-7745	en_US
dc.contributor.author	Yang, LT	en_US
dc.date.issued	2010-11-19	en_US
dc.identifier.citation	Proceedings - 10th IEEE International Conference on Computer and Information Technology, CIT-2010, 7th IEEE International Conference on Embedded Software and Systems, ICESS-2010, ScalCom-2010, 2010, pp. 511 - 516	en_US
dc.identifier.isbn	9780769541082	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16285
dc.description.abstract	Automatic License Plate Recognition is useful for real time traffic management and surveillance. License plate recognition usually contains two steps, namely license plate detection/localization and character recognition. Recognizing characters in a license plate is a very difficult task due to poor illumination conditions and rapid motion of vehicles. When using an OCR for character recognition, it is crucial to correctly remove the license plate boundaries after the step for license plate detection. No matter which OCRs are used, the recognition accuracy will be significantly reduced if the boundaries are not properly removed. This paper presents an efficient algorithm for non character area removal. The algorithm is based on the license plates detected using an AdaBoost algorithm. Then it follows the steps of character height estimation, character width estimation, segmentation and block identification. The algorithm is efficient and can be applied in real-time applications. The experiments are performed using OCR software for character recognition. It is shown that much higher recognition accuracy is obtained by gradually removing the license plate boundaries. © 2010 IEEE.	en_US
dc.relation.ispartof	Proceedings - 10th IEEE International Conference on Computer and Information Technology, CIT-2010, 7th IEEE International Conference on Embedded Software and Systems, ICESS-2010, ScalCom-2010	en_US
dc.relation.isbasedon	10.1109/CIT.2010.111	en_US
dc.title	Accuracy enhancement for license plate recognition	en_US
dc.type	Conference Proceeding
utslib.for	0806 Information Systems	en_US
dc.location.activity	Bradford, West Yorkshire UK	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
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Automatic License Plate Recognition is useful for real time traffic management and surveillance. License plate recognition usually contains two steps, namely license plate detection/localization and character recognition. Recognizing characters in a license plate is a very difficult task due to poor illumination conditions and rapid motion of vehicles. When using an OCR for character recognition, it is crucial to correctly remove the license plate boundaries after the step for license plate detection. No matter which OCRs are used, the recognition accuracy will be significantly reduced if the boundaries are not properly removed. This paper presents an efficient algorithm for non character area removal. The algorithm is based on the license plates detected using an AdaBoost algorithm. Then it follows the steps of character height estimation, character width estimation, segmentation and block identification. The algorithm is efficient and can be applied in real-time applications. The experiments are performed using OCR software for character recognition. It is shown that much higher recognition accuracy is obtained by gradually removing the license plate boundaries. © 2010 IEEE.

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http://hdl.handle.net/10453/16285