License Plate Detection Using Neural Networks

  • Luis Carrera
  • Marco Mora
  • José Gonzalez
  • Francisco Aravena
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5518)


This work presents a new method for license plate detection using neural networks in gray scale images. The method proposes a multiple classification strategy based on a Multilayer Perceptron. It consists of many classifications of one image using several shifted window grids. If a pixel belongs or not to the licence plate is determined by the most frequent answer given by the different classifications. The result becomes more precise by means of morphological operations and heuristic rules related to shape and size of the license plate zone. The whole method detects the license plates precisely with a low error rate under non-controlled environments.


Intelligence Transportation System Heuristic Rule License Plate Pulse Couple Neural Network Frequent Answer 
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 2009

Authors and Affiliations

  • Luis Carrera
    • 1
  • Marco Mora
    • 1
  • José Gonzalez
    • 2
  • Francisco Aravena
    • 2
  1. 1.Les Fous du Pixel Image Processing Research Group Department of Computer ScienceCatholic University of MauleTalcaChile
  2. 2.TUTELKANTalcaChile

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