This paper presents a vehicle license plate recognition method based on character-specific extremal regions (ERs) and hybrid discriminative restricted Boltzmann machines (HDRBMs). First, coarse license plate detection (LPD) is performed by top-hat transformation, vertical edge detection, morphological operations, and various validations. Then, character-specific ERs are extracted as character regions in license plate candidates. Followed by suitable selection of ERs, the segmentation of characters and coarse-to-fine LPD are achieved simultaneously. Finally, an offline trained pattern classifier of HDRBM is applied to recognize the characters. The proposed method is robust to illumination changes and weather conditions during 24 h or one day. Experimental results on thorough data sets are reported to demonstrate the effectiveness of the proposed approach in complex traffic environments.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Vehicle License Plate Recognition Based on Extremal Regions and Restricted Boltzmann Machines


    Beteiligte:
    Gou, Chao (Autor:in) / Wang, Kunfeng (Autor:in) / Yao, Yanjie (Autor:in) / Li, Zhengxi (Autor:in)


    Erscheinungsdatum :

    01.04.2016


    Format / Umfang :

    3061949 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






    LICENSE PLATE RECOGNITION BASED VEHICLE CONTROL

    NISHIMURA HIROAKI / GEORGIS NIKOLAOS | Europäisches Patentamt | 2022

    Freier Zugriff

    Vehicle License Plate Registration Recognition System

    Tiruneh, Embiale Merkebu ;Jiang, De Ning | Trans Tech Publications | 2013