Detecting the wheel pattern of a vehicle using stereo images

Mun K. Leung, Thomas S. Huang

Research output: Contribution to journalArticlepeer-review


This paper presents a method for detecting the wheels of a vehicle in stereo image pairs. The method consists of two steps: (i) geometrical transformation; and (ii) circle extraction. The geometrical transformation uses the disparity values obtained from a stereo image pair to calculate the parameters of the plane containing wheels of the vehicle. By using these parameters, we transform any elliptical wheels contained in the plane to circular ones which can be extracted by the circle extraction algorithm. The circle extraction algorithm consists of (1) template matching and (2) Hough transform. In order to save computation and improve the results in the Hough transform, we employ two constraints (a) the neighbor-region edge connectivity and (b) the gradient direction of each edge point, to eliminate non-circular edge points. Experimental results show that these two constraints do eliminate non-circular edge points and preserve any circle embedded in edges. From the final results, we can observe that our method can detect and locate the wheels of a vehicle successfully.

Original languageEnglish (US)
Pages (from-to)1139-1151
Number of pages13
JournalPattern Recognition
Issue number12
StatePublished - 1991


  • Circle extraction
  • Edge connectivity
  • Geometrical transformation
  • Gradient direction
  • Hough transform
  • Zero-crossing

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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