Multi-feature fusion based circular traffic sign detection

Jing Zhang, Ming Yi He, Yu Chao Dai, Xiao Gang Qu

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Based on color and shape features of circular traffic sign, a multi-feature fusion based circular traffic sign detection algorithm is proposed. Firstly, color segmentation and achromatic decomposition are used to extract area containing circular traffic signs, and thus most of the background area is eliminated. Then, edge detection is applied, and the output edges are stored by chain code. Features, including length of contour, circularity and aspect ratio, are used to further eliminate background area. Finally, according to the shape feature of circular traffic sign, nonlinear least squares method is employed to detect the exact traffic signs. Effectiveness of the proposed algorithm is demonstrated preliminarily on real images captured under various weather and illumination conditions.

Original languageEnglish
Pages (from-to)226-232
Number of pages7
JournalMoshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence
Volume24
Issue number2
StatePublished - Apr 2011

Keywords

  • Achromatic decomposition
  • Circle detection
  • Contour coding
  • Curve fitting

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