Multiple Clues for License Plate Detection and Recognition

  • Pablo Negri
  • Mariano Tepper
  • Daniel Acevedo
  • Julio Jacobo
  • Marta Mejail
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6419)

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.

Keywords

Support Vector Machine Optical Character Recognition License Plate Text Segment Character Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Pablo Negri
    • 1
  • Mariano Tepper
    • 2
  • Daniel Acevedo
    • 2
  • Julio Jacobo
    • 2
  • Marta Mejail
    • 2
  1. 1.PLADEMAUniversidad del Centro de la Provincia de Buenos AiresTandilArgentina
  2. 2.Departamento de Computación-Facultad de Ciencias Exactas y NaturalesUniversidad de Buenos AiresArgentina

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