Vehicle License Plate Detection (VLPD) is the most critical stage of any vehicle License Plate Recognition (LPR) system because it has a direct impact on its robustness and accuracy. As a result, VLPD remains a difficult task because vehicle license plates (VLP) vary in size, axes, orientation, and may be occluded or have their locations changed. In this paper, we present our framework for an image-based VLPD system based on morphological information and deep learning. To address this issue, we created a new "YellowLP" dataset with 1050 images of unique and different rear VLP numbers. Pecision, recall, and overall accuracy of the morphological results are 98.65%, 97.90%, and 96.61%, respectively, with a detection rate of 97.90%. Deep learning increases the recall and overall accuracy of the proposed approach to 100% and 98.65%, respectively. As an outcome, the proposed method produced acceptable results.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Vehicle license plate detection using morphological operations and deep learning


    Beteiligte:
    Hezil, Nabil (Autor:in) / Amrouche, Aissa (Autor:in) / Bentrcia, Youssouf (Autor:in)


    Erscheinungsdatum :

    26.11.2022


    Format / Umfang :

    1774196 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Localization of License Plate Using Morphological Operations

    Karthikeyan, V. / Vijayalakshmi, V. J. | ArXiv | 2014

    Freier Zugriff

    Improved license plate localisation algorithm based on morphological operations

    Yepez, Juan / Ko, Seok-Bum | IET | 2018

    Freier Zugriff

    Improved license plate localisation algorithm based on morphological operations

    Yepez, Juan / Ko, Seok‐Bum | Wiley | 2018

    Freier Zugriff

    Automatic vehicle license plate number detection using machine learning

    Rondla, Saikiran Reddy | BASE | 2020

    Freier Zugriff