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dc.contributor.authorSotudeh, Reza
dc.contributor.authorZhai, Xiaojun
dc.contributor.authorBensaali, Faycal
dc.date.accessioned2015-12-14T11:13:13Z
dc.date.available2015-12-14T11:13:13Zen
dc.date.issued2013-11-01
dc.identifier.citationZhai, X, Bensaali, F, & Sotudeh, R n.d., 'Real-time optical character recognition on field programmable gate array for automatic number plate recognition system', Iet Circuits Devices & Systems, 7, 6, pp. 337-344en
dc.identifier.issn1751-858X
dc.identifier.issn1751-8598
dc.identifier.doi10.1049/iet-cds.2012.0339
dc.identifier.urihttp://hdl.handle.net/10545/583882
dc.description.abstractThe last main stage in an automatic number plate recognition system (ANPRs) is optical character recognition (OCR), where the number plate characters on the number plate image are converted into encoded texts. In this study, an artificial neural network-based OCR algorithm for ANPR application and its efficient architecture are presented. The proposed architecture has been successfully implemented and tested using the Mentor Graphics RC240 field programmable gate arrays (FPGA) development board equipped with a 4M Gates Xilinx Virtex-4 LX40. A database of 3570 UK binary character images have been used for testing the performance of the proposed architecture. Results achieved have shown that the proposed architecture can meet the real-time requirement of an ANPR system and can process a character image in 0.7 ms with 97.3% successful character recognition rate and consumes only 23% of the available area in the used FPGA.
dc.language.isoenen
dc.publisherThe Institution of Engineering and Technologyen
dc.relation.ispartofseriesVol. 7en
dc.relation.ispartofseriesIssue 6en
dc.relation.urlhttp://digital-library.theiet.org/content/journals/10.1049/iet-cds.2012.0339en
dc.rightsArchived with thanks to IET Circuits, Devices & Systemsen
dc.subjectImage processingen
dc.subjectFPGAen
dc.subjectField programmable gate arraysen
dc.subjectOptical character recognitionen
dc.subjectNeural netsen
dc.subjectUK binary character imagesen
dc.subjectANPR applicationen
dc.subjectNumber plate charctersen
dc.titleReal-time optical character recognition on field programmable gate array for automatic number plate recognition systemen
dc.typeArticleen
dc.contributor.departmentUniversity of Hertfordshireen
dc.identifier.journalIET Circuits, Devices & Systemsen
html.description.abstractThe last main stage in an automatic number plate recognition system (ANPRs) is optical character recognition (OCR), where the number plate characters on the number plate image are converted into encoded texts. In this study, an artificial neural network-based OCR algorithm for ANPR application and its efficient architecture are presented. The proposed architecture has been successfully implemented and tested using the Mentor Graphics RC240 field programmable gate arrays (FPGA) development board equipped with a 4M Gates Xilinx Virtex-4 LX40. A database of 3570 UK binary character images have been used for testing the performance of the proposed architecture. Results achieved have shown that the proposed architecture can meet the real-time requirement of an ANPR system and can process a character image in 0.7 ms with 97.3% successful character recognition rate and consumes only 23% of the available area in the used FPGA.


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