Multiple Clues for License Plate Detection and Recognition

PABLO NEGRI; MARIANO TEPPER; DANIEL ACEVEDO; JULIO JACOBO; MARTA MEJAIL

San Pablo

Congreso; Iberoamerican Congress on Pattern Recognition; 2010

International Association of Pattern Recognition (IAPR)

p, li { white-space: pre-wrap; } 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 \textit{a contrario} framework using the shape contexts as features and the other based on a SVM classifier using the intensity pixel values as features.