Abstract
Machine vision systems that perform inspection tasks must be capable of making measurements. A vision system measures an image to determine a measurement of the object being viewed. The image measurement depends on several factors, including sensing, image processing, and feature extraction. We consider the error that can occur in measuring the distance between two corner points of the 2D image. We analyze the propagation of the uncertainty in edge point position to the 2D measurements made by the vision system, from 2D curve extraction, through point determination, to measurement. We extend earlier work on the relationship between random perturbation of edge point position and variance of the least squares estimate of line parameters and analyze the relationship between the variance of 2D points.
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References
Albano A (1974) Representation of digitized contours in terms of conic arcs and straight-line segments. Comput Graph Image Processing 4:23–33
Biggerstaff RH (1972) Three variations in dental arch form estimated by a quadratic equation. Dent Res 51:1509
Bookstein FL (1979) Fitting conic sections to scattered data. Comput Graph Image Processing 9:56–71
Cooper DR, Yalabik N (1976) On the computational cost of approximating and recognizing noise-perturbed straight lines and quadratic arcs in the plane. IEEE Trans Comput C25:1020
Gnanadesikan R (1977) Methods for statistical data analysis of multivariate observations. Wiley, New York
Gordon G (1970) System simulation. Prentice Hall, Englewood Cliffs
Haralick RM (1989) Line fitting. Unpublished manuscript, Intelligent Systems Laboratory, Department of Electrical Engineering, University of Washington, Seattle
Hogg RV, Craig AJ (1978) Introduction to mathematical statistics. Macmillan, New York
Ott L (1984) An Introduction to statistical methods and data analysis. Duxbury, Boston, MA
Paton KA (1970) Conic sections in automatic chromosome analysis. Mach Intell 5
Paton KA (1970) Conic sections in chromsome analysis. Patt Recogn 2:39
Payne J (1982) Introduction to simulation. McGraw-Hill, New York
Yi S (1990) Illumination and control expert for machine vision: a goal driven approach. PhD Dissertation, Department of Computer Science and Engineering, University of Washington, Seattle, WA
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Yi, S., Haralick, R.M. & Shapiro, L.G. Error propagation in machine vision. Machine Vis. Apps. 7, 93–114 (1994). https://doi.org/10.1007/BF01215805
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DOI: https://doi.org/10.1007/BF01215805