Autor(es)

Pablo Negri and Mariano Tepper and Daniel Acevedo and Julio Jacobo and Marta Mejail

URL Pública

Abstract

This paper addresses a license plate detection and recognition (LPR) task on still images of trucks. The main contribution of our LPR system is the fusion of different segmentation algorithms used to improve the license plate detection. We also compare the performance of two kinds of classifiers for optical character recognition (OCR): one based on the a contrario framework using the shape contexts as features and the other based on a SVM classifier using the intensity pixel values as features.