{"title":"基于距离图像的车辆分类系统","authors":"Shiquan Peng, C. Harlow","doi":"10.1109/SSST.1996.493523","DOIUrl":null,"url":null,"abstract":"In this project we consider automated vehicle location and classification systems. Current systems which utilize loop detectors or video cameras have deficiencies. Video based systems are sensitive to environmental conditions and do not perform well in vehicle classification. The new generation of range or distance sensors that are being developed offer the promise of sensors which are not sensitive to lighting conditions and provide information which should give better vehicle detection and classification percentages than current systems. The focus of this project is to develop an automated vehicle location and classification system based upon imagery obtained from range sensors. Image analysis operators and classification methods are developed for vehicle classification. Preliminary results indicate that accurate vehicle classification can be obtained.","PeriodicalId":135973,"journal":{"name":"Proceedings of 28th Southeastern Symposium on System Theory","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A system for vehicle classification from range imagery\",\"authors\":\"Shiquan Peng, C. Harlow\",\"doi\":\"10.1109/SSST.1996.493523\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this project we consider automated vehicle location and classification systems. Current systems which utilize loop detectors or video cameras have deficiencies. Video based systems are sensitive to environmental conditions and do not perform well in vehicle classification. The new generation of range or distance sensors that are being developed offer the promise of sensors which are not sensitive to lighting conditions and provide information which should give better vehicle detection and classification percentages than current systems. The focus of this project is to develop an automated vehicle location and classification system based upon imagery obtained from range sensors. Image analysis operators and classification methods are developed for vehicle classification. Preliminary results indicate that accurate vehicle classification can be obtained.\",\"PeriodicalId\":135973,\"journal\":{\"name\":\"Proceedings of 28th Southeastern Symposium on System Theory\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 28th Southeastern Symposium on System Theory\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSST.1996.493523\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 28th Southeastern Symposium on System Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSST.1996.493523","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A system for vehicle classification from range imagery
In this project we consider automated vehicle location and classification systems. Current systems which utilize loop detectors or video cameras have deficiencies. Video based systems are sensitive to environmental conditions and do not perform well in vehicle classification. The new generation of range or distance sensors that are being developed offer the promise of sensors which are not sensitive to lighting conditions and provide information which should give better vehicle detection and classification percentages than current systems. The focus of this project is to develop an automated vehicle location and classification system based upon imagery obtained from range sensors. Image analysis operators and classification methods are developed for vehicle classification. Preliminary results indicate that accurate vehicle classification can be obtained.