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Vehicle Number Plates Detection and Recognition using improved Algorithms: A Review with Tanzanian Case study

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dc.contributor.author Munuo, Cosmo H.
dc.contributor.author Kisangiri, Michael
dc.date.accessioned 2019-08-28T05:41:15Z
dc.date.available 2019-08-28T05:41:15Z
dc.date.issued 2014-05
dc.identifier.issn 2319-7242
dc.identifier.uri http://dspace.nm-aist.ac.tz/handle/123456789/433
dc.description Research Article published by International Journal Of Engineering And Computer Science Volume 3 Issue 5, May 2014 en_US
dc.description.abstract Invented in 1976, Number Plates Recognition (NPR) has since found wide commercial applications, making its research prospects challenging and scientifically interesting. A complete NPR system functions by vz steps, license plate; localization, sizing and orientation, normalization, character recognitions and geometric analysis. This paper is a review of NPR preliminary stages; it explains number plate localization, sizing and orientations as well as normalizations sections of the Number Plates Detection and Recognition-Tanzania Case study. MATLAB R2012b is employed in these processes. The input incorporated includes front and rear photographic images of vehicles, for proximity and simulation purposes the ample angle of image is 90 degree +-15. The captured image is converted to gray scale, binarized and edge detection algorithms are used to enhance edges. The output of this stage provides the input feature extraction, segmentation and recognitions. en_US
dc.language.iso en en_US
dc.publisher International Journal Of Engineering And Computer Science en_US
dc.subject gray scale en_US
dc.subject thresholding en_US
dc.subject edge detection en_US
dc.subject number plate en_US
dc.title Vehicle Number Plates Detection and Recognition using improved Algorithms: A Review with Tanzanian Case study en_US
dc.type Article en_US


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