B. V. Ghaffari, T. Kitajima, S. S. Abdullah, M. Kouhnavard
{"title":"A robust and highly efficient localization method for irregular license plates","authors":"B. V. Ghaffari, T. Kitajima, S. S. Abdullah, M. Kouhnavard","doi":"10.1109/TENCONSPRING.2014.6863109","DOIUrl":null,"url":null,"abstract":"This paper presents a robust method for license plate localization (LPL). Basically, the performance of LPL directly affects the accuracy of License Plate Recognition system. Although many studies had been conducted on LPL systems, many of them only discuss on license plate (LP) from countries that have restricted and distinguished LP types in terms of shapes and fonts. In this paper, a novel LPL system is proposed to address difficulties in recognizing extraordinary LP types with respect to shapes and fonts. The system has been implemented using MATLAB in eight different conditions of illumination in an actual environment to illustrate the efficiency of the proposed method. The total accuracy of this system for all conditions is 96% to 97%.","PeriodicalId":270495,"journal":{"name":"2014 IEEE REGION 10 SYMPOSIUM","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE REGION 10 SYMPOSIUM","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TENCONSPRING.2014.6863109","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a robust method for license plate localization (LPL). Basically, the performance of LPL directly affects the accuracy of License Plate Recognition system. Although many studies had been conducted on LPL systems, many of them only discuss on license plate (LP) from countries that have restricted and distinguished LP types in terms of shapes and fonts. In this paper, a novel LPL system is proposed to address difficulties in recognizing extraordinary LP types with respect to shapes and fonts. The system has been implemented using MATLAB in eight different conditions of illumination in an actual environment to illustrate the efficiency of the proposed method. The total accuracy of this system for all conditions is 96% to 97%.