Segmentation and recognition of traffic signs using shape information

  • Authors:

  • Jun-Taek Oh;Hyun-Wook Kwak;Young-Ho Sohn;Wook-Hyun Kim

  • Affiliations:

  • School of EECS, Yeungnam University, Gyeongbuk, South Korea;School of EECS, Yeungnam University, Gyeongbuk, South Korea;School of EECS, Yeungnam University, Gyeongbuk, South Korea;School of EECS, Yeungnam University, Gyeongbuk, South Korea

  • Venue:
  • ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
  • Year:
  • 2005

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Abstract

This paper proposes a method for traffic sign recognition and segmentation using shape information of traffic sign. First, a connected component algorithm is used to segment candidate traffic sign regions from a binary image obtained based on the RGB color ratio of each pixel in image. Then actual traffic sign regions are segmented based on their X- and Y-axes symmetry. The recognition step utilizes shape information, including a moment, edge correlogram, and the number of times a concentric circular pattern from the region center intersects with the frequency information extracted by the wavelet transform. Finally, recognition is performed by measuring the similarity with templates in a database. Experimental results confirm the validity of the proposed method as regards geometric transformations and environmental factors.