Due to the prodigious road traffic, many cities experience road congestions. Hence, there is a requirement of efficient and automatic road traffic analysis. The computer vision (CV) technique is one of the rapidly utilized fields for traffic analysis. This paper proposes a system that efficiently tracks and counts the number of vehicles for automatic traffic monitoring. The system is composed of several stages viz. demosaicing on Bayer filter pattern video frames, moving object algorithm for vehicle detection, and Blob analysis is for tracking and counting of vehicles on a road. The prepossessing is performed with the help of system generator development tool of Xilinx, and the tracking & counting of vehicles on a road are observed in the MATLAB Simulink environment. The algorithms are applied to all the frames in every video with the labeled vehicle is shown. An average accuracy of 98.78% is obtained on real time videos captured through different traffic conditions. The comparison with the similar reported algorithms validates the superiority of the proposed work for traffic analysis system.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Automatic Road Traffic Analyzer using Background Subtraction, Blob Analysis, and Tracking Algorithms




    Publication date :

    2023-10-27


    Size :

    564876 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Aerial Based Traffic Tracking and Vehicle Count Detection Using Background Subtraction

    Muhamad, Muhamad Zulhilmi Bin / Akhtar, Mohammad Nishat / Bakar, Elmi Abu et al. | Springer Verlag | 2022


    Aerial Based Traffic Tracking and Vehicle Count Detection Using Background Subtraction

    Muhamad, Muhamad Zulhilmi Bin / Akhtar, Mohammad Nishat / Bakar, Elmi Abu et al. | TIBKAT | 2022


    Smart Traffic Management System using Background Subtraction

    Kottha, Bharath Reddy / T, Anuradha / Penumacha, Naveen Kumar et al. | IEEE | 2024


    Comparative study of background subtraction algorithms

    Benezeth, Y. / Jodoin, P.-M. / Emile, B. et al. | British Library Online Contents | 2010