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To control of geometrical parameters of large size double curvature objects using computer vision system

https://doi.org/10.21285/1814-3520-2019-4-670-677

Abstract

The purpose of the paper is justification of possible control of geometrical parameters of big size double curvature objects using an optical grid imposed by means of the projector and the analysis of the received image by means of a video camera and applied software. Various geometric shapes of the optical grid projected on the measured surface are studied. An algorithm of optical grid formation and superposition depending on the shape of the controlled surface is developed. The type of video camera for taking video images is studied. The mutual position of the project and the camera is investigated, the relationship between the position of the video camera and the projector is revealed and various geometric shapes of the optical grid are studied. The application of various geometrical shapes of the optical grid to control double curvature surfaces is substantiated. Optimal points for the installation of the project and the video camera to read the geometric parameters of the controlled surface are selected. Conducted experiments allowed to find out that rectangular grids are most suitable for the control of parts with a smoothly changing surface curvature, while the polyhedron grid is more suitable for the parts with the sharply changing curvature of the surface. It is also determined that the accuracy of surface geometric parameter control depends on the resolution of the video camera used and the relative position of the camera and the projector.

About the Authors

D. A. Bublik
Irkutsk National Research Technical University
Russian Federation


R. V. Kononenko
Irkutsk National Research Technical University
Russian Federation


Review

For citations:


Bublik D.A., Kononenko R.V. To control of geometrical parameters of large size double curvature objects using computer vision system. Proceedings of Irkutsk State Technical University. 2019;23(4):670-677. (In Russ.) https://doi.org/10.21285/1814-3520-2019-4-670-677

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ISSN 2782-4004 (Print)
ISSN 2782-6341 (Online)