License plate recognition (LPR) is composed of license plate detection (LPD), character segmentation, and character recognition. In this paper, we put forward a license plate recognition (LPR) system. For license plate detection (LPD), a hybrid algorithm based on colour and shape is proposed (HLPD). For character segmentation, taking into account the horizontal preliminary information of the black and white histogram, a cross-zero search character segmentation algorithm based on the black and white histogram is suggested (CCZA). For character recognition, 10 sets of CNN models with different frameworks are proposed. The CCCP-BN-DP performs best when compared to the performance of the test set. The HLPD-CCZA-CCCP-BN-DP system is then applied to the public data set CCPD and experiments demonstrate the effectiveness of the LPR system.


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    Titel :

    License plate recognition system based on the difference of convolutional neural network framework


    Beteiligte:
    Li, Zhihong (Autor:in) / Zhang, Jing (Autor:in) / Wen, Yanjie (Autor:in)


    Erscheinungsdatum :

    08.10.2022


    Format / Umfang :

    722228 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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