• DocumentCode
    2840935
  • Title

    Detection for triangle traffic sign based on neural network

  • Author

    Zhu, Shuang-Dong ; Zhany, Yi ; Lu Xiao-feng

  • Author_Institution
    Fac. of Inf. Sci. & Technol., Ningbo Univ., China
  • fYear
    2005
  • fDate
    14-16 Oct. 2005
  • Firstpage
    25
  • Lastpage
    28
  • Abstract
    This literature critically explains the intelligent method for detection of traffic signs. This method uses a particular color and shape for the detection of traffic signs, as an example, we used red color down triangle shape traffic sign, to explain this method. This method is mainly carried out in four steps, which are as follows. First, convert RGB color space to HIS color space, and extract pixels with red color. Then perform LOG mask operation on the pixels got from step 1, for the detection of edges. By using neural network, we determine the angle pixels, and at the same time, we also determine on which specific angle the pixel is. And finally we detect the traffic sign by using the information of shape. We used 20 different images from different scenes to test this method, and the percentage of correctness is 100%.
  • Keywords
    edge detection; image colour analysis; neural nets; road traffic; traffic engineering computing; RGB color space; edge detection; neural network; red color down triangle shape traffic sign; triangle traffic sign detection; Image edge detection; Image recognition; Layout; Machine intelligence; Neural networks; Nonlinear distortion; Pollution; Shape; Telecommunication traffic; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicular Electronics and Safety, 2005. IEEE International Conference on
  • Print_ISBN
    0-7803-9435-6
  • Type

    conf

  • DOI
    10.1109/ICVES.2005.1563608
  • Filename
    1563608