• DocumentCode
    3310592
  • Title

    Character Recognition System Based on Back-Propagation Neural Network

  • Author

    Li, Fuliang ; Gao, Shuangxi

  • fYear
    2010
  • fDate
    24-25 April 2010
  • Firstpage
    393
  • Lastpage
    396
  • Abstract
    According to the characteristics of vehicle license plate, recognition algorithm was proposed based on back-propagation (BP) neural network. Classifier was divided into Chinese characters classifier, English letters classifier, English letters and numbers mixed classifier, and digital classifier these four kinds of classifier in the algorithm. This neural network design can effectively simplify the network structure, improved recognition accuracy and speed. BP algorithm went along improvement as the defects of the standard BP algorithm which had slow convergence and easy to fall into local minimum points. Through simulation experiments, the character recognition system not only has a higher recognition rate, but also has better neural network robustness to decrease failures, that is having good robustness characteristics.
  • Keywords
    Artificial neural networks; Backpropagation algorithms; Character recognition; Educational institutions; Feedforward neural networks; Licenses; Multi-layer neural network; Neural networks; Neurons; Vehicles; BP network; character recognition; ehicle license plate;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Vision and Human-Machine Interface (MVHI), 2010 International Conference on
  • Conference_Location
    Kaifeng, China
  • Print_ISBN
    978-1-4244-6595-8
  • Electronic_ISBN
    978-1-4244-6596-5
  • Type

    conf

  • DOI
    10.1109/MVHI.2010.185
  • Filename
    5532900