{"title":"Fast license plate detection based on edge density and integral edge image","authors":"P. Tarábek","doi":"10.1109/SAMI.2012.6208994","DOIUrl":null,"url":null,"abstract":"This paper presents a robust algorithm for license plate detection that can detect multiple license plates with various sizes in unfamiliar and complex backgrounds. License plate detection is an important processing step in license plate recognition which has many applications in intelligent transportation systems. Vertical edges and edge density features are utilized to find candidate regions. Then, the candidates are filtered out based on geometrical and textural properties. The efficiency of the method is improved using the integral edge image and two-stage candidate window detection. The experimental results confirm robustness and efficiency of proposed method.","PeriodicalId":158731,"journal":{"name":"2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMI.2012.6208994","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25
Abstract
This paper presents a robust algorithm for license plate detection that can detect multiple license plates with various sizes in unfamiliar and complex backgrounds. License plate detection is an important processing step in license plate recognition which has many applications in intelligent transportation systems. Vertical edges and edge density features are utilized to find candidate regions. Then, the candidates are filtered out based on geometrical and textural properties. The efficiency of the method is improved using the integral edge image and two-stage candidate window detection. The experimental results confirm robustness and efficiency of proposed method.