Simulation process for the design and optimization of a machine vision system for specular surface inspection

Ralph Seulin; Nicholas Bonnot; Fred Merienne; Patrick Gorria

doi:10.1117/12.455250

11 February 2002 Simulation process for the design and optimization of a machine vision system for specular surface inspection

Ralph Seulin, Nicholas Bonnot, Fred Merienne, Patrick Gorria

Author Affiliations +

Proceedings Volume 4567, Machine Vision and Three-Dimensional Imaging Systems for Inspection and Metrology II; (2002) https://doi.org/10.1117/12.455250
Event: Intelligent Systems and Advanced Manufacturing, 2001, Boston, MA, United States

Abstract

This work aims at detecting surface defects on reflecting industrial parts. A machine vision system, performing the detection of geometric aspect surface defects, is completely described. The revealing of defects is realized by a particular lighting device. It has been carefully designed to ensure the imaging of defects. The defects segmentation is then straightforward and fast to compute. The imaging conditions have been particularly studied because they influence strongly the quality of acquired images and consequently the quality of image processing results. These imaging conditions are often the fact of experiments: numerous attempts on lighting features and on the relative positions between the cameras, the lighting and the object are still necessary. To bring help in the conception of these imaging conditions, a complete simulation is proposed. The imaging and lighting system has been completely modeled. The simulation, based on computer graphics, enables here the rendering of realistic images. Simulation provides a very efficient way of conception which is applied to the design of a machine vision prototype.

Citation Download Citation

Ralph Seulin, Nicholas Bonnot, Fred Merienne, and Patrick Gorria "Simulation process for the design and optimization of a machine vision system for specular surface inspection", Proc. SPIE 4567, Machine Vision and Three-Dimensional Imaging Systems for Inspection and Metrology II, (11 February 2002); https://doi.org/10.1117/12.455250

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