{"title":"A Computer Vision Based on Vehicle Detection and Counting System Using Sensor Security","authors":"Prashant Kumar, Shilpi Sharma","doi":"10.1109/RDCAPE52977.2021.9633454","DOIUrl":null,"url":null,"abstract":"Unique—Vehicle identification and counting framework, which assumes a significant part in keen transportation framework, and the administration of the progression of traffic. In this real, we refuse a video metric technique for the place and whole of vehicles self-reliant on PC vision innovations. The proposed lack employs the foundation deduction strategy is to see closer view objects into the video. For a more precise recognition of moving vehicles, and afterward there are some PC vision strategies, including tear an opening to fill, and keeping in mind that the morphology of the exercises. At long last, the vehicle, the statistics will be done with the assistance of a virtual discovery zone. The trial results show ordinarily the exactness and precision of the deliberate vehicle counting framework, it is around 96%.","PeriodicalId":424987,"journal":{"name":"2021 4th International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 4th International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RDCAPE52977.2021.9633454","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Unique—Vehicle identification and counting framework, which assumes a significant part in keen transportation framework, and the administration of the progression of traffic. In this real, we refuse a video metric technique for the place and whole of vehicles self-reliant on PC vision innovations. The proposed lack employs the foundation deduction strategy is to see closer view objects into the video. For a more precise recognition of moving vehicles, and afterward there are some PC vision strategies, including tear an opening to fill, and keeping in mind that the morphology of the exercises. At long last, the vehicle, the statistics will be done with the assistance of a virtual discovery zone. The trial results show ordinarily the exactness and precision of the deliberate vehicle counting framework, it is around 96%.