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dc.contributor.authorMunuo, Cosmo H.
dc.contributor.authorMichael, Kisangiri
dc.contributor.authorNvungi, Nerey H.
dc.date.accessioned2019-08-28T06:25:32Z
dc.date.available2019-08-28T06:25:32Z
dc.date.issued2014
dc.identifier.issn2222-2863
dc.identifier.urihttp://dspace.nm-aist.ac.tz/handle/123456789/437
dc.descriptionResearch Article published by Computer Engineering and Intelligent Systems Vol.5, No.10, 2014en_US
dc.description.abstractThe growing Tanzanian population currently estimated to be 48 Million people and their use of vehicles as means of transport has kept increasing making enforcing traffic rules and regulations among road users a major challenge. This calls for a need to have an automated system that monitors the motorists with a pre-defined sense of intelligence. A Vehicle Detection and Recognition Algorithm which can provide automated access to relevant information to a number plate from information systems containing and managing databases on vehicle and their movements is required. This paper presents work on developed algorithm that localizes plate area, extract and segment character, and finally recognizes and interprets registration number from vehicle image. MATLAB R2012b Simulation software with Image Processing toolbox is employed. HSV color space image, morphological and statistical analysis operations were integrated and employed to a vehicle image to compute plate number area. In segmentation the properties like aspect ratio, extent, and area ratio were important measurement parameters. Finally, the template matching database and statistical character extracted from car image was correlated to recognize alphanumeric character to deduce car registration number.en_US
dc.language.isoenen_US
dc.publisherComputer Engineering and Intelligent Systemsen_US
dc.subjectCharacter extractionen_US
dc.subjectDetection algorithmen_US
dc.subjectRecognition algorithmen_US
dc.subjectMorphological matchingen_US
dc.subjectTemplate matchingen_US
dc.titleVehicle Plate Number Detection and Recognition Using Improved Algorithmen_US
dc.typeArticleen_US


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