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        • Colombia
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        • Universidad Tecnológica de Bolivar UTB (Colombia)
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        • Colombia
        • Universidades
        • Universidad Tecnológica de Bolivar UTB (Colombia)
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        Automatic recognition of Colombian car license plates using convolutional neural networks and Chars74k database

        Fecha
        2020
        Registro en:
        Arroyo-Pérez, D. E., Alvarez-Canchila, O. I., Patĩo-Saucedo, A., Rostro González, H., & Patĩo-Vanegas, A. (2020). Automatic recognition of colombian car license plates using convolutional neural networks and Chars74k database. Paper presented at the Journal of Physics: Conference Series, , 1547(1) doi:10.1088/1742-6596/1547/1/012024
        https://hdl.handle.net/20.500.12585/9384
        10.1088/1742-6596/1547/1/012024
        Universidad Tecnológica de Bolívar
        Repositorio Universidad Tecnológica de Bolívar
        Autor
        Arroyo-Pérez, D E
        Álvarez-Canchila, O I
        Patiño-Saucedo, A
        Rostro González, H
        Patiño Vanegas, Alberto
        Institución
        • Universidad Tecnológica de Bolivar UTB (Colombia)
        Resumen
        A methodology for the automatic recognition of Colombian car license plates using convolutional neural networks is proposed. One of the biggest challenges when using onvolutional neural network is the demand for large amounts of samples for training. In this work, we show that if we do not have enough images of vehicle license plates to carry out the training, we can complement it with databases of letters and numbers that are not extracted from cars. The network was trained with the Chars74k database and images of characters extracted from plates of Colombian automobiles. The Chars74k contains approximately 74000 images of all the letters of the Spanish alphabet and all digits from 0 to 9. From chars74k database we have chosen 33849, because the Colombian plates have only uppercase letters and digits. Only 3549 (about 10% of the total) images of characters extracted manually from plates of Colombian automobiles were added. At the input of the convolutional neural network, 70% of the images were used for training, 20% for validation and 10% for testing and the resulting validation accuracy was above 99%. By making a preliminary test on Colombian plates never before used in training, a percentage of correctly recognized plates above 98% was achieved.
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        Red de Repositorios Latinoamericanos
        + de 8.000.000 publicaciones disponibles
        500 instituciones participantes
        Dirección de Servicios de Información y Bibliotecas (SISIB)
        Universidad de Chile
        Ingreso Administradores
        Colecciones destacadas
        • Tesis latinoamericanas
        • Tesis argentinas
        • Tesis chilenas
        • Tesis peruanas
        Nuevas incorporaciones
        • Argentina
        • Brasil
        • Colombia
        • México
        Dirección de Servicios de Información y Bibliotecas (SISIB)
        Universidad de Chile
        Red de Repositorios Latinoamericanos | 2006-2018