In this paper, we propose an intelligent system for identification and classification of parking vehicles. The proposed system uses artificial intelligence and pattern matching to identify and classify various types of vehicles for optimizing the use of parking lot space, monitor incoming and outgoing vehicles, and increase profit. The system uses image processing and feature extraction techniques to extract features such as vehicle dimensions and estimated weights to determine the vehicles eligibility to park in a specific parking lot given some restrictions and constraints. A prototype was developed and implemented in MATLAB/SIMULINK, and we validated all algorithms for accuracy purposes considering different classes of the vehicle. Preliminary results have shown that the system is effective and promising in different conditions.


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    Titel :

    Intelligent Parking Vehicle Identification and Classification System


    Beteiligte:
    Kumar, Amit K. (Autor:in) / Assaf, Mansour H. (Autor:in) / Groza, Voicu Z. (Autor:in) / Petriu, Emil M. (Autor:in)


    Erscheinungsdatum :

    01.07.2021


    Format / Umfang :

    1826359 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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