• DocumentCode
    2486066
  • Title

    Geometrical, Physical and Text/Symbol Analysis Based Approach of Traffic Sign Detection System

  • Author

    Liu, Yangxing ; Ikenaga, Takeshi ; Goto, Satoshi

  • Author_Institution
    Graduate Sch. of Inf., Production & Syst., Waseda Univ., Kitakyushu
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    238
  • Lastpage
    243
  • Abstract
    Traffic sign detection is a valuable part of future driver support system. In this paper, we present a novel framework to accurately detect traffic signs from a single color image by analyzing geometrical, physical and text/symbol features of traffic signs. First, we utilize an elaborate edge detection algorithm to extract edge map and accurate edge pixel gradient information. Second 2D geometric primitives (circles, ellipses, rectangles and triangles) are quickly extracted from image edge map. Third the candidate traffic sign regions are selected by analyzing the intrinsic color features, which are invariant to different illumination conditions, of each region circumvented by geometric primitives. Finally a text and symbol detection algorithm is introduced to classify true traffic signs. Experimental results demonstrated the capabilities of our algorithm to detect traffic signs with respect to different size, shape, color and illumination conditions
  • Keywords
    edge detection; feature extraction; geometry; image colour analysis; text analysis; traffic engineering computing; 2D geometric primitives; color image analysis; driver support system; edge detection; edge map extraction; edge pixel gradient information; geometrical analysis; physical analysis; symbol analysis; text analysis; traffic sign detection system; Data mining; Image analysis; Image color analysis; Image edge detection; Layout; Lighting; Robustness; Shape; Vehicle detection; Vehicle driving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium, 2006 IEEE
  • Conference_Location
    Tokyo
  • Print_ISBN
    4-901122-86-X
  • Type

    conf

  • DOI
    10.1109/IVS.2006.1689635
  • Filename
    1689635