Detection of laser induced optical defects based on image segmentation

A number of vision-based methods for detecting laser-induced defects on optical components have been implemented to replace the time-consuming manual inspection. While deep-learning-based methods have achieved state-of-the-art performances in many visual recognition tasks, their success often hinges on the availability of a large number of labeled training sets. In this paper, we propose a surface defect detection method based on image segmentation with a U-shaped convolutional network (U-Net).