Automatic Recognition of Peruvian Car License Plates

Sebastian Escalante, Victor Murray

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

Some of the applications of automatic license plate recognition algorithms are security, tracking, and toll collection. However, due to the lack of regulations on Peruvian car license plates, developing a robust system to detect them represents a challenge. The problem is not only related to different rules based on vehicle types or rule year inconsistencies but also that many vehicles on the road have degraded license plates or thick protectors that hinder the character recognition process. In this manuscript, we present an optimized method based on the k-nearest neighbors (k-NN) classification method, which is compared with regular k-NN and multiclass support vector machines to recognize Peruvian car license plates, with accuracy results bigger than 96% for the optimized k-NN method.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728193779
DOI
EstadoPublicada - set. 2020
Publicado de forma externa
Evento27th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020 - Virtual, Lima, Perú
Duración: 3 set. 20205 set. 2020

Serie de la publicación

NombreProceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020

Conferencia

Conferencia27th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020
País/TerritorioPerú
CiudadVirtual, Lima
Período3/09/205/09/20

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