Paper Title
APPLICATION OF ARTIFICIAL INTELLIGENCE ON DETECTING GLASS DEFECTS

Abstract
This study introduced an artificial intelligent technique into the automated optical inspection (AOI) system for glass inspection. The inspection targets included two types of glass defects, namely scratch and chip. The image acquisition system was optimized to capture the features of defects with the most suitable light source and setup. In the image processing algorithm, YOLOv4 was considered for the inspection application Two approaches were used to optimize the YOLOv4 model, namely fine-tuning and anchor box optimization. The most accurate model was the YOLOv4 optimized by anchor box and trained with the input size of 960 × 960 pixels. Moreover, it could effectively exclude non-defect objects. With these results,the developed inspection system could detect defects as small as a scratch of 0.05-mm width and a chip of 0.1 mm. Keywords - Automated Optical Inspection, Artificial Intelligent, Defect Detection, Glass, YOLO.