{"title":"Detecting wheels of vehicle in stereo images","authors":"M. K. Leung, Thomas S. Huang","doi":"10.1109/ICPR.1990.118108","DOIUrl":null,"url":null,"abstract":"A method for detecting the wheels of a vehicle in stereo image pairs is presented. The method consists of two steps: geometrical transformation and 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. These parameters are used to 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 template matching and the Hough transform. In order to save computation and improve the results in the Hough transform, two constraints, the neighbor-region edge connectivity and the gradient direction of each edge point, are used to eliminate noncircular edge points. Experimental results show that these two constraints do eliminate noncircular edge points and preserve any circle embedded in edges. The final results show that the proposed method can detect and locate the wheels of a vehicle successfully.<<ETX>>","PeriodicalId":135937,"journal":{"name":"[1990] Proceedings. 10th International Conference on Pattern Recognition","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1990] Proceedings. 10th International Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.1990.118108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
A method for detecting the wheels of a vehicle in stereo image pairs is presented. The method consists of two steps: geometrical transformation and 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. These parameters are used to 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 template matching and the Hough transform. In order to save computation and improve the results in the Hough transform, two constraints, the neighbor-region edge connectivity and the gradient direction of each edge point, are used to eliminate noncircular edge points. Experimental results show that these two constraints do eliminate noncircular edge points and preserve any circle embedded in edges. The final results show that the proposed method can detect and locate the wheels of a vehicle successfully.<>