Over the last decade, the number of automobiles has skyrocketed. There are more than one billion active automobiles in the universe, including 70–80 million in India. Handling such traffic conditions and providing enough parking spaces is a difficult task. Vehicle counting and classification on congested routes will assist authorities in obtaining traffic flow data as well as understanding and studying traffic patterns, allowing for the most efficient traffic management. As a result, the aim of this work is that a cost-effective vision-based vehicle counting and classification system that is mainly implemented in OpenCV utilising Python programming and some methods of image processing.


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    Titel :

    Vehicle Classification and Counting from Surveillance Camera Using Computer Vision


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Suma, V. (Herausgeber:in) / Baig, Zubair (Herausgeber:in) / Kolandapalayam Shanmugam, Selvanayaki (Herausgeber:in) / Lorenz, Pascal (Herausgeber:in) / Ayub khan, A. (Autor:in) / Sabeenian, R. S. (Autor:in) / Janani, A. S. (Autor:in) / Akash, P. (Autor:in)


    Erscheinungsdatum :

    02.08.2022


    Format / Umfang :

    14 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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