Traffic a significant problem in a lot of cities at different places due to increase in number of vehicles. For traffic related problems, computer vision approaches are preferable. System during any installation will not trouble traffic and are easily changed. We proposed an advance vehicle detection, vehicle classification and vehicle counting system for traffic analysis. Input either image or a video. First detection and classification of vehicles takes place followed by vehicle count. In this project, we detect and classify heavy motor and light motor vehicles like car, motorbike, truck, bus on the roads and also count the number of vehicles travel through the roads. YOLOv4 model, Configuration file and Weight file of YOLOv4, COCO dataset, Non Max Suppression and OpenCV are used to implement the system. Counted data is stored in file to analyze different vehicles that are traveling through the roads which is used for analysis and diversion.


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    Titel :

    Image and Video Processing-Based Traffic Analysis Using OpenCV


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Bhateja, Vikrant (Herausgeber:in) / Mohanty, Jnyana Ranjan (Herausgeber:in) / Flores Fuentes, Wendy (Herausgeber:in) / Maharatna, Koushik (Herausgeber:in) / Pooja Sri, Devineni (Autor:in) / Kiran Kumar, K. (Autor:in)


    Erscheinungsdatum :

    2022-10-28


    Format / Umfang :

    7 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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