Geometrical, physical and text/symbol analysis based approach of traffic sign detection system

Yangxing Liu, Takeshi Ikenaga, Satoshi Goto

Research output: Contribution to journalArticle

11 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)208-216
Number of pages9
JournalIEICE Transactions on Information and Systems
VolumeE90-D
Issue number1
DOIs
Publication statusPublished - 2007 Jan

Keywords

  • Geometrical analysis
  • Physical analysis
  • Text detection
  • Traffic sign detection

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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