A Survey of Industrial Surface Defect Detection Based on Deep Learning

Surface defect detection in industrial production is crucial. Traditional image processing techniques face limitations when dealing with complex textures, background noise, and lighting variations. As deep learning technology advances, its applications across various fields have become increasingly widespread, displaying notable benefits in terms of performance in real time and great precision. the utilization of deep learning for the detection of surface defects in industrial settings. According to the metal surface, texture surface and other surfaces of industrial surface defect detection, three aspects of defect segmentation, defect detection and defect classification are studied in detail. By analyzing and comparing different methods, we explore the practical effects of deep learning technology in various industrial surface defect detections, highlighting current challenges and potential future directions.