Auto Rack Girders Assembly Holes Measurement Based on Multi-camera Vision
Since single camera’s visual field is limited, the measurement method for auto rack girders assembly holes based on multi-group of binocular vision is proposed. The measurement area is divided into several subregions, the measurement data of each subregion is obtained from the binocular vision measurement system, and a larger planar target is used to achieve three-dimensional data registration among adjacent subregion. Since the texture information of truck side-member surface is not abundant, it is difficult to seek the match points on the edge of assembly holes. It is proposed that pasting marked points around the edge of assembly holes for seeking match points. Every two marked points can be connected into one line, and the intersections of the lines and assembly holes’ edge are seen as match points. At last, the geometric parameters of spatial circle are fitted according to its geometrical properties. Experimental results show that the matching difficulty will be avoided effectively, the measurement error caused by perspective projection distortion can be reduced, and the method has higher measurement accuracy.
KeywordsFeature points Assembly holes Planar target
This work was supported by Jilin province science and technology development funding project. The title of the research project: On-line Inspection Key Technology Research for the Train Wheelset Manufacture Quality, and project serial number: 20160204005GX.
- 3.Zhang JX et al (1996) Application technology of binocular stereo vision in industrial detection. Tianjin University, TianjinGoogle Scholar
- 5.Lins RG, Kurka PRG (2013) Architecture for multi-camera vision system for automated measurement of automotive components. In: 7th annual IEEE international systems conference, pp 520–527Google Scholar
- 7.Prasad DK, Leung MKH, Quek C et al (2013) ElliFit: an unconstrained, non-iterative, least squares based geometric Ellipse Fitting method. Pattern Recogn: J Pattern Recogn Soc 46(5):1449–1465Google Scholar
- 8.Li YS, Yang F, Yuan ZK et al (2013) A detection method for 3D circle fitting. Sci Surveying Mapp 38(6):147–148Google Scholar