• DocumentCode
    3439634
  • Title

    Detection and recognition of road signs using simple layered neural networks

  • Author

    Ohara, Harofumi ; Nishikawa, Ikuko ; Miki, Shigeto ; Yabuki, Noboru

  • Author_Institution
    Dept. of Comput. Sci., Ritsumeikan Univ., Shiga, Japan
  • Volume
    2
  • fYear
    2002
  • fDate
    18-22 Nov. 2002
  • Firstpage
    626
  • Abstract
    A road sign detection method is proposed, using 2 simple 3-layered neural networks. Multiple preprocessing steps are taken for masking the irrelevant areas and selecting the candidate areas from an original input color images, and both neural networks are modules for this selection process. One network is for matching a color of an input pixel with a road sign, and the other is for matching a shape of an input object. The final recognition is given by a template matching, and an auxiliary re-detection step is added to improve the efficiency. The experiments using a large number of pictured images under several different conditions show the high detection rates over 95% in most cases, while the computational cost is low owing to the smallness and the simplicity of the neural networks.
  • Keywords
    feedforward neural nets; image colour analysis; image matching; object recognition; road traffic; traffic engineering computing; color images; color matching; multilayered neural networks; multiple preprocessing; neural networks; road sign recognition; template matching; Brightness; Color; Computer science; Data preprocessing; Filters; Image processing; Neural networks; Pixel; Roads; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
  • Print_ISBN
    981-04-7524-1
  • Type

    conf

  • DOI
    10.1109/ICONIP.2002.1198133
  • Filename
    1198133