{"title":"A laser intensity image based automatic vehicle classification system","authors":"H. Abdelbaki, K. Hussain, E. Gelenbe","doi":"10.1109/ITSC.2001.948701","DOIUrl":null,"url":null,"abstract":"This paper presents a laser intensity image based algorithm for automatic vehicle classification system (AVC) on highways. The algorithm performs line by line processing of laser intensity images, produced by laser sensory units, and extracts vehicle features used for the classification. The features include vehicle length, width, height, speed, and some distinguishable patterns in the vehicle profile. The proposed technique outperforms the range data technique in deteriorated atmospheric conditions (such as rain and fog). A software package with a graphical user interface has been developed to illustrate the usage of the classification algorithm and to evaluate its performance.","PeriodicalId":173372,"journal":{"name":"ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"49","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2001.948701","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 49
Abstract
This paper presents a laser intensity image based algorithm for automatic vehicle classification system (AVC) on highways. The algorithm performs line by line processing of laser intensity images, produced by laser sensory units, and extracts vehicle features used for the classification. The features include vehicle length, width, height, speed, and some distinguishable patterns in the vehicle profile. The proposed technique outperforms the range data technique in deteriorated atmospheric conditions (such as rain and fog). A software package with a graphical user interface has been developed to illustrate the usage of the classification algorithm and to evaluate its performance.