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Genetic Algorithm Based Neural Network for License Plate Recognition

  • Wang Xiaobin
  • Li Hao
  • Wu Lijuan
  • Hong Qu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7951)

Abstract

This paper combines genetic algorithms and neural networks to recognize vehicle license plate characters. We train the neural networks using a genetic algorithm to find optimal weights and thresholds. The traditional genetic algorithm is improved by using a real number encoding method to enhance the networks weight and threshold accuracy. At the same time, we use a variety of crossover operations in parallel, which broadens the range of the species and helps the search for the global optimal solution. An adaptive mutation rate both ensures the diversity of the species and makes the algorithm convergence more rapidly to the global optimum. Experiments show that this method greatly improves learning efficiency and convergence speed.

Keywords

license plate recognition genetic algorithms neural networks character recognition 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Wang Xiaobin
    • 1
  • Li Hao
    • 1
  • Wu Lijuan
    • 1
  • Hong Qu
    • 1
  1. 1.Computational Intelligence Laboratory, School of Computer Science and EngineeringUniversity of Electronic Science and Technology of ChinaChina

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