OCR based feature extraction and template matching algorithms for Qatari number plate

Hdl Handle:
http://hdl.handle.net/10545/620809
Title:
OCR based feature extraction and template matching algorithms for Qatari number plate
Authors:
Farhat, Ali; Al-Zawqari, Ali; Al-Qahtani, Abdulhadi; Hommos, Omar; Bensaali, Faycal ( 0000-0002-9273-4735 ) ; Amira, Abbes; Zhai, Xiaojun ( 0000-0002-1030-8311 )
Abstract:
There are several algorithms and methods that could be applied to perform the character recognition stage of an automatic number plate recognition system; however, the constraints of having a high recognition rate and real-time processing should be taken into consideration. In this paper four algorithms applied to Qatari number plates are presented and compared. The proposed algorithms are based on feature extraction (vector crossing, zoning, combined zoning and vector crossing) and template matching techniques. All four proposed algorithms have been implemented and tested using MATLAB. A total of 2790 Qatari binary character images were used to test the algorithms. Template matching based algorithm showed the highest recognition rate of 99.5% with an average time of 1.95 ms per character.
Affiliation:
University of Derby
Citation:
Farhat, A. et al (2016) 'OCR based feature extraction and template matching algorithms for Qatari number plate', Proceedings of the International Conference on Industrial Informatics and Computer Systems (CIICS), Sharjah-Dubai, United Arab Emirates, 13th - 15th March
Publisher:
IEEE
Journal:
Proceedings of the International Conference on Industrial Informatics and Computer Systems (CIICS)
Issue Date:
13-Mar-2016
URI:
http://hdl.handle.net/10545/620809
DOI:
10.1109/ICCSII.2016.7462419
Additional Links:
http://ieeexplore.ieee.org/document/7462419/; http://www.aus.edu/ciics16; http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7457953
Type:
Meetings and Proceedings
Language:
en
Series/Report no.:
15956672
Appears in Collections:
Department of Electronics, Computing & Maths

Full metadata record

DC FieldValue Language
dc.contributor.authorFarhat, Alien
dc.contributor.authorAl-Zawqari, Alien
dc.contributor.authorAl-Qahtani, Abdulhadien
dc.contributor.authorHommos, Omaren
dc.contributor.authorBensaali, Faycalen
dc.contributor.authorAmira, Abbesen
dc.contributor.authorZhai, Xiaojunen
dc.date.accessioned2016-11-11T10:48:48Z-
dc.date.available2016-11-11T10:48:48Z-
dc.date.issued2016-03-13-
dc.identifier.citationFarhat, A. et al (2016) 'OCR based feature extraction and template matching algorithms for Qatari number plate', Proceedings of the International Conference on Industrial Informatics and Computer Systems (CIICS), Sharjah-Dubai, United Arab Emirates, 13th - 15th Marchen
dc.identifier.doi10.1109/ICCSII.2016.7462419-
dc.identifier.urihttp://hdl.handle.net/10545/620809-
dc.description.abstractThere are several algorithms and methods that could be applied to perform the character recognition stage of an automatic number plate recognition system; however, the constraints of having a high recognition rate and real-time processing should be taken into consideration. In this paper four algorithms applied to Qatari number plates are presented and compared. The proposed algorithms are based on feature extraction (vector crossing, zoning, combined zoning and vector crossing) and template matching techniques. All four proposed algorithms have been implemented and tested using MATLAB. A total of 2790 Qatari binary character images were used to test the algorithms. Template matching based algorithm showed the highest recognition rate of 99.5% with an average time of 1.95 ms per character.en
dc.language.isoenen
dc.publisherIEEEen
dc.relation.ispartofseries15956672en
dc.relation.urlhttp://ieeexplore.ieee.org/document/7462419/en
dc.relation.urlhttp://www.aus.edu/ciics16en
dc.relation.urlhttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7457953en
dc.subjectOptical character recognitionen
dc.subjectFeature extractionen
dc.subjectImage segmentationen
dc.subjectAlgorithmen
dc.titleOCR based feature extraction and template matching algorithms for Qatari number plateen
dc.typeMeetings and Proceedingsen
dc.contributor.departmentUniversity of Derbyen
dc.identifier.journalProceedings of the International Conference on Industrial Informatics and Computer Systems (CIICS)en
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