Automatic recognition of Colombian car license plates using convolutional neural networks and Chars74k database

D. E. Arroyo-Pérez, O. I. Alvarez-Canchila, A. Patĩo-Saucedo, H. Rostro González, A. Patĩo-Vanegas

Producció científica: Article en revista indexadaArticle de conferènciaAvaluat per experts

1 Citació (Scopus)

Resum

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.

Idioma originalAnglès
Número d’article012024
RevistaJournal of Physics: Conference Series
Volum1547
Número1
DOIs
Estat de la publicacióPublicada - 18 de juny 2020
Publicat externament
Esdeveniment16th National Meeting on Optics, ENO 2019 and 7th Andean and Caribbean Conference on Optics and Its Applications, CANCOA 2019 - Monteria, Colombia
Durada: 26 de nov. 201930 de nov. 2019

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