{"title":"Pattern matching approach towards real-time traffic sign recognition","authors":"H. Fleyeh, Taha Khan","doi":"10.1109/MCIT.2010.5444852","DOIUrl":null,"url":null,"abstract":"This paper addresses the problem of traffic sign recognition in real-time conditions. The algorithm presented in this paper is based on detecting traffic signs in life images and videos using pattern matching of the unknown sign's shape with standard shapes of the traffic signs. The pattern matching algorithm works with shape vertices rather than the whole image. This reduces the computation time which is a crucial factor to fit real-time demands. The algorithm is translation and scaling invariant. It shows high robustness as it is tested with 500 images and several videos and a recognition rate of 97% is achieved.","PeriodicalId":285648,"journal":{"name":"2010 International Conference on Multimedia Computing and Information Technology (MCIT)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Multimedia Computing and Information Technology (MCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MCIT.2010.5444852","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper addresses the problem of traffic sign recognition in real-time conditions. The algorithm presented in this paper is based on detecting traffic signs in life images and videos using pattern matching of the unknown sign's shape with standard shapes of the traffic signs. The pattern matching algorithm works with shape vertices rather than the whole image. This reduces the computation time which is a crucial factor to fit real-time demands. The algorithm is translation and scaling invariant. It shows high robustness as it is tested with 500 images and several videos and a recognition rate of 97% is achieved.