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In the field of industrial vision, the three-dimensional inspection of highly reflective metallic objects is still a delicate task. We deal with a new automated three-dimensional inspection system based on polarization analysis. We first present an extension of the shape-from-polarization method for dielectric surfaces to metallic surfaces. Then, we describe what we believe to be a new way of solving the ambiguity concerning the normal orientation with an active lighting system. Finally, applications to shape-defect detection are discussed, and the efficiency of the system to discriminate defects on specular metallic objects made by stamping and polishing is presented.

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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 lighting system simplifies a lot the image processing for defect segmentation and so a real-time inspection of reflective products is possible. To bring help in the conception of imaging conditions, a complete simulation is proposed. The simulation, based on computer graphics, enables the rendering of realistic images. Simulation provides here a very efficient way to perform tests compared to the numerous attempts of manual experiments