• Title of article

    Traffic Road Sign Detection and Classification

  • Author/Authors

    Fartaj، Mehdi نويسنده Department of Electrical Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran. , , Ghofrani، Sedigheh نويسنده Electrical Engineering Department, South Tehran Branch, Islamic Azad University, Tehran, Iran ,

  • Issue Information
    فصلنامه با شماره پیاپی 23 سال 2012
  • Pages
    9
  • From page
    54
  • To page
    62
  • Abstract
    Traffic road sign detection is important to a robotic vehicle that automatically drives on roads. As the colors of most traffic road signs are blue and red, in this paper, we use Hue- Saturation- Intensity (HSI) color space for color based segmentation at first. Using important geometrical features, the road signs are detected perfectly. After segmentation, it turns to classify every detected road signs. For this purpose, we employ and compare the performance of three classifiers; they are distance to border (DTB), FFT sample of signature, and code matrix. In this work, we use the code matrix as an efficient classifier for the first time. Although the achieved accuracy by code matrix is greater than the two referred classifiers in average, the main advantage is simplicity and so less computational cost.
  • Journal title
    Majlesi Journal of Electrical Engineering
  • Serial Year
    2012
  • Journal title
    Majlesi Journal of Electrical Engineering
  • Record number

    1596986