With the continuous development of social economy, the per capita car ownership has increased rapidly, and the traffic congestion problem followed has become increasingly serious. In order to process the video information of intersections effectively, this paper completed the design of vehicle target detection and statistics algorithm based on the characteristics of video images in the green light duration. Firstly, a suitable image preprocessing algorithm is designed. Secondly, the improved mixture Gaussian background modeling algorithm is used to perform background subtraction, and the target vehicles are extracted. At the same time, the circumscribed rectangular frame is used to identify the vehicle. Finally, the total number of vehicles of the entire video is counted by calculating the number of vehicles running in the current frame. The experimental results show that the algorithm has a high detection rate and has certain practicability.


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    Titel :

    Dynamic vehicle target detection and traffic statistics algorithm research


    Beteiligte:
    Liu, Changyuan (Autor:in) / Ren, Yuyan (Autor:in) / Hong, Luning (Autor:in)

    Kongress:

    Eleventh International Conference on Digital Image Processing (ICDIP 2019) ; 2019 ; Guangzhou,China


    Erschienen in:

    Proc. SPIE ; 11179


    Erscheinungsdatum :

    14.08.2019





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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