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dc.contributor.authorFarhat, Ali
dc.contributor.authorAl-Zawqari, Ali
dc.contributor.authorAl-Qahtani, Abdulhadi
dc.contributor.authorHommos, Omar
dc.contributor.authorBensaali, Faycal
dc.contributor.authorAmira, Abbes
dc.contributor.authorZhai, Xiaojun
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.
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
html.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.


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