Vehicle classification is one of the main focuses in traffic survey work. In this paper, an influenced recognition model of vehicle class was proposed and experimented on using the feature extraction of vehicle's time-domain sound signal, considering the existing problems like costly equipments, low efficiency in operation, and difficulty of data analysis, etc. According to vehicle's sound signal waveform characteristics, it is shown that the changed point can be obtained by analyzing the short-time energy and zero-crossing rate in time-domain, and then the vehicle class can be determined. The simulated experimental results indicate that the proposed method is simple and economical to recognize vehicle class. The statistic precision can correspond with the need of the engineering.


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    Titel :

    Vehicle Class Recognition Based on Vehicle's Sound Signal


    Beteiligte:
    Gao, Han (Autor:in) / Xue, Liang (Autor:in) / Zhang, Cuiling (Autor:in)

    Kongress:

    Second International Conference on Transportation Information and Safety ; 2013 ; Wuhan, China


    Erschienen in:

    ICTIS 2013 ; 898-903


    Erscheinungsdatum :

    2013-06-11




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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