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

  • Authors:

  • Yangxing Liu;Takeshi Ikenaga;Satoshi Goto

  • Affiliations:

  • The authors are with the Graduate School of Information, Production and Systems, Waseda University, Kitakyushu-shi, 808--0135 Japan. E-mail: lyx@ruri.waseda.jp;The authors are with the Graduate School of Information, Production and Systems, Waseda University, Kitakyushu-shi, 808--0135 Japan. E-mail: lyx@ruri.waseda.jp;The authors are with the Graduate School of Information, Production and Systems, Waseda University, Kitakyushu-shi, 808--0135 Japan. E-mail: lyx@ruri.waseda.jp

  • Venue:
  • IEICE - Transactions on Information and Systems
  • Year:
  • 2007

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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. Then, we extract 2-D geometric primitives (circles, ellipses, rectangles and triangles) efficiently 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.