Lighting study for an optimal defects detection by artificial vision

Claudine Coulot; Sophie Kohler-Hemmerlin; Christophe Dumont; Denis Aluze; Bernard Lamalle

doi:10.1117/12.271249

15 April 1997 Lighting study for an optimal defects detection by artificial vision

Claudine Coulot, Sophie Kohler-Hemmerlin, Christophe Dumont, Denis Aluze, Bernard Lamalle

Proceedings Volume 3029, Machine Vision Applications in Industrial Inspection V; (1997) https://doi.org/10.1117/12.271249
Event: Electronic Imaging '97, 1997, San Jose, CA, United States

Abstract

Lighting, which is an important side of quality control by artificial vision is often neglected. Scientists have to spend time and make several experiments before finding a good solution. We have chosen to study lighting of metallic objects according to the shape and the roughness of the object for an optimal defect detection. The first step of our study was to find a theoretical model of light scattering. To take into account reflection on smooth as well as rough surfaces, it is necessary to have a physical approach in the way of Beckmann and Spizzichino who based their model on electromagnetic wave theory. The general expression for surface radiance is a fairly complicated function of the angles of incidence and reflection, and the surface roughness parameters. Radiance diagrams of this model give the light intensity reflected by an elementary surface in all the directions. Thanks to this model, we are able to optimize the size and position of the source according to the shape and the roughness of the object and the type of defects to detect. In the field of artificial vision, the conceivable applications are numerous: for instance one can quote defect detection (scratches, knocks...) or dimensional control of object (swell or undulation measurement...).

Citation Download Citation

Claudine Coulot, Sophie Kohler-Hemmerlin, Christophe Dumont, Denis Aluze, and Bernard Lamalle "Lighting study for an optimal defects detection by artificial vision", Proc. SPIE 3029, Machine Vision Applications in Industrial Inspection V, (15 April 1997); https://doi.org/10.1117/12.271249

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