Varsha Kshirsagar-Deshpande, T. Patel, Ali Abbas, Khushbhu Bhatt, R. Bhalerao, Jiten Shah
{"title":"Vehicle Tracking Using Morphological Properties for Traffic Modelling","authors":"Varsha Kshirsagar-Deshpande, T. Patel, Ali Abbas, Khushbhu Bhatt, R. Bhalerao, Jiten Shah","doi":"10.1109/InGARSS48198.2020.9358966","DOIUrl":null,"url":null,"abstract":"In the proposed method, an innovative image processing technique for vehicle tracking at a roundabout is described. Background subtraction is applied to get the objects (vehicles) in the foreground. The objects are thus obtained and tracked using morphological operations and object properties. In the video stream, tracking is established by tracing the center of the target object. In present case,four different directions of incoming traffic are considered and four vehicle classes are defined. Implementation of above mentioned method achieved promising result of accuracy greater than 90 % for moderate traffic conditions where occlusion is not an issue.","PeriodicalId":6797,"journal":{"name":"2020 IEEE India Geoscience and Remote Sensing Symposium (InGARSS)","volume":"10 1","pages":"98-101"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE India Geoscience and Remote Sensing Symposium (InGARSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/InGARSS48198.2020.9358966","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In the proposed method, an innovative image processing technique for vehicle tracking at a roundabout is described. Background subtraction is applied to get the objects (vehicles) in the foreground. The objects are thus obtained and tracked using morphological operations and object properties. In the video stream, tracking is established by tracing the center of the target object. In present case,four different directions of incoming traffic are considered and four vehicle classes are defined. Implementation of above mentioned method achieved promising result of accuracy greater than 90 % for moderate traffic conditions where occlusion is not an issue.