Accurate Dimensional Measurement of 3D Round Holes Based on Stereo Vision
This paper present an effective method to accurately reconstruct and measure the 3D curve edges of small industrial parts based on stereo vision. To effectively fit the curve of the measured parts using a series of line segments in the images, a strategy from coarse to fine is employed based on multi-scale curve fitting. After reconstructing the 3D curve of a hole through a curved surface, its axis is adjusted so that it is parallel to the Z axis with least squares error and the dimensions of the hole can be calculated on the XY plane easily. Experimental results show that the presented method can accurately measure the dimensions of round holes through a curved surface.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1057447Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1239
 C. Y. Lin, A New Approach to Automatic Reconstruction of a 3-D World Using Active Stereo Vision. Computer Vision and Image Understanding, 2002. 85(2): p. 117-143.
 S Pollard and J Porrill, Robust recovery of 3D ellipse data. Brrtish Machine Vision Conf, 1992: p. 39-48.
 A. Wozniak and M. Dobosz, Factors Influencing Probing Accuracy of a Coordinate Measuring Machine. IEEE Transactions on Instrumentation and Measurement, 2005. 54(6).
 H. Shimotahira, K.I., S. C. Chu, C. Wah, F. Costen, and Y. Yoshikuni, Three-dimensional laser microvision. Applied Optics, 2001. 40(11): p. 1784-1794.
 S. Komatsu, H.S., and H. Ohzu, Laser scanning microscope with a differential heterodyne optical probe. Applied Optics, 1990. 29(28): p. 4244-4249.
 Z. Y. Wang, H.D., S. Park, and H. M. Xie, Three-dimensional shape measurement with a fast and accurate approach. Applied Optics, 2009. 48(6).
 R. Anchini, C.L., V. Paciello, and A. Paolillo, A Comparison Between Stereo-Vision Techniques for the Reconstruction of 3-D Coordinates of Objects. IEEE Transactions on Instrumentation and Measurement, 2006. 55(5).
 R. O. Duda and P. E. Hart, Use of the Hough Transform to detect lines and curves in pictures. Communications of the ACM, 1972. 15(1).
 A Leonardis and R Bajcsy, Finding parametric curves in an image. Second European Conf. Computer Visron,, 1992: p. 653-657.
 A. Albano, Representation of digitised contours in terms of conic arcs and straight line segments. Computer Graphics and Image Processing, 1974. 5: p. 23-33.
 Y Nakagawa and A Rosenfeld, A note on polygonal and elliptical approximation of mechanical parts. Pattern Recognition, 1979. 11: p. 133-142.
 Pavlidis, T., Curve fitting with conic splines. ACM Trans Graphics,, 1983. 2(1): p. 1-31.
 P.L. Rosin, G.A.W.W., Nonparametric Segmentation of Curves into Various Representations. IEEE Transactions on Pattern Analysis and Machine Intelligence 1995. 17(12): p. 1140-1153.
 Y-Z Liao, A two-stage method of fitting conic arcs and straight line segments to digitised contours. Conf. Pattern Recognition and Image Processing, 1981: p. 224-229.
 I. Weiss, Line Fitting in a Noisy Image. IEEE Transaction on Pattern Analysis and Machine Intelligence, 1989. 2(3).
 H. Qjidaa and L. Radouane, Robust Line Fitting in a Noisy Image by the Method of Moments. IEEE Transaction on Pattern Analysis and Machine Intelligence, 1999. 21(11).
 S. H. Park, K.M.L., and S. U. Lee, A Line Feature Matching Technique Based on an Eigenvector Approach. Computer Vision and Image Understanding, 2000. 77(3): p. 263-283.
 H. H. Joon, S.P.J., Contour Matching Using Epipolar Geometry. IEEE Trans. on Pattern Anal. Machine Intell., 2000. 22(4).