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基于vc的车牌识别系统.docx


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Abstract
With the development of economy all over the world, the number on the vehicle is increasing sharply in many countries. The transportation is a hard problem to settle. Many experts all over the world are studying on ITS(Intelligent Transportation System) in order to improve the efficacy of transportation. VLPR(Vehicle License Plate Recognition) is a key technique about ITS and one of major topics of puter vision and pattern recognition in the field of ITS. The information of the vehicle will be clear when the license plate is learned because it’s the unique identification of vehicle.
Automatic identification system consists of image processing module, plate positioning module, characters division module and characters recognition module, including follow-up application development. According to different modules, this paper researches and analyzes
the existing theories and algorithms, and puts forward a practical solution scheme of application significance. We use VC++ as the develop language realize the relate algorithm during the image preprocessing and VLPR.
This paper is mainly divided into following several modules:
Picture pretreatment module: This pleted is the edge detection of the vehicle license pictures, binarization, median filtering etc. It builds the foundation for the behind recognition work.
Vehicle license localization module: This module locates the license plate in
the auto mobile picture. In this module, we bring a new locating method, which is based on multiplespot-matching.
Characters division module: According to the result of the location of the vehicle license plate , considering of the clearances between the character and
between the characters and the edge of width of the character and the width of the license plate is different ,we project the image in the direction of horizon and vertical, wipe off the edge of the license ,segment the characters.
Characters recognition module: Considering of the character feature in the

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  • 页数71
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  • 上传人wz_198613
  • 文件大小776 KB
  • 时间2018-05-15