A machine vision system for defect characterization on transparent parts with non-plane surfaces

This contribution presents a machine vision system capable of revealing, detecting and characterizing defects on non-plane transparent surfaces. Because in this kind of surface, transparent and opaque defects can be found, special lighting conditions are required. Therefore, the cornerstone of this machine vision is the innovative lighting system developed. Thanks to this, the defect segmentation is straightforward and with a very low computational burden, allowing real-time inspection. To aid in the conception of the imaging conditions, the lighting system is completely described and also compared with other commercial lighting systems. In addition, for the defect segmentation, a new adaptive threshold selection algorithm is proposed. Finally, the system performance is assessed by conducting a series of tests using a commercial model of headlamp lens.