The number of vehicles is steadily rising right now, which causes an increase in traffic accidents and crime. The younger generations are still engaging in reckless driving, despite the fact that the government has implemented legislation and traffic regulations to lower the number of accidents and fatalities on the roads. As a result, it is critical to implement. An automated system to keep a watch on the rapid vehicles and take subsequent actions. The primary goal of the study is to develop the system in practice using the kNN, Pytesseract that is currently available. This model first detects the presence of cars, then calculates their speeds, and lastly decodes the number plates of the fast-moving automobiles. The report offers an analysis of the effectiveness of the implemented method via comparisons using various video datasets.


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    Titel :

    Real-time Vehicle Count, Speed Estimation and Number Plate Detection using CCTV Footage


    Beteiligte:
    Gaikwad, P. S. (Autor:in) / Chaudhari, Pratik (Autor:in) / Bhole, Pragati (Autor:in) / Girhe, Vinayak (Autor:in) / Karekar, Aniruddh (Autor:in)


    Erscheinungsdatum :

    27.04.2023


    Format / Umfang :

    1042956 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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