• DocumentCode
    396751
  • Title

    A design of the object detection system using the RGA

  • Author

    Yoshimori, Seiki ; Mitsukura, Yasue ; Fukumi, Minotu ; Akamatsu, Norio

  • Author_Institution
    Tokushima Univ., Japan
  • Volume
    2
  • fYear
    2003
  • fDate
    20-24 July 2003
  • Firstpage
    1227
  • Abstract
    License plate recognition is very important is an automobile society. However, it is very difficult to do it, because the background and body color of cars are sometimes similar to that of the license plate. Furthermore, the detection of cars moving at a very high speed is difficult. In this paper, we propose a new robust thresholds-determination method in various backgrounds by using the real coded genetic algorithm (RGA). By using RGA, the most likely plate colors are decided under various light conditions. First, the average brightness Y values of images are calculated. Next, relationship between the Y value and the most likely plate color thresholds (upper and lower bounds) are obtained by GA to estimate threshold equations by using recursive least squares (RLS) algorithm. Finally, in order to show the effectiveness of the proposed method, we show simulation examples by using real images. The resulting rate of detection is 85.0%.
  • Keywords
    edge detection; genetic algorithms; image colour analysis; least squares approximations; road vehicles; average image brightness; background color; body color; license plate recognition; light conditions; object detection system; plate colors; real coded genetic algorithm; recursive least squares algorithm; robust thresholds-determination method; Automobiles; Brightness; Equations; Genetic algorithms; Least squares approximation; Licenses; Object detection; Recursive estimation; Resonance light scattering; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2003. Proceedings of the International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7898-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2003.1223868
  • Filename
    1223868