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

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dc.creator Munuo, Cosmo H.
dc.creator Michael, Kisangiri
dc.date 2019-08-28T05:41:15Z
dc.date 2019-08-28T05:41:15Z
dc.date 2014-05
dc.date.accessioned 2022-10-25T09:15:57Z
dc.date.available 2022-10-25T09:15:57Z
dc.identifier 2319-7242
dc.identifier http://dspace.nm-aist.ac.tz/handle/123456789/433
dc.identifier.uri http://hdl.handle.net/123456789/94721
dc.description Research Article published by International Journal Of Engineering And Computer Science Volume 3 Issue 5, May 2014
dc.description 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.
dc.format application/pdf
dc.language en
dc.publisher International Journal Of Engineering And Computer Science
dc.subject gray scale
dc.subject thresholding
dc.subject edge detection
dc.subject number plate
dc.title Vehicle Number Plates Detection and Recognition using improved Algorithms: A Review with Tanzanian Case study
dc.type Article


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