基于计算机视觉的工业金属表面缺陷检测综述

Focusing on the industrial surface defect detection of metal planar and three-dimensional structural materials, this paper summarizes the basic principle and research status of visual defect detection technology, and summarizes the key technologies of visual automatic detection system including optical imaging technology, image preprocessing technology and defect detector. Firstly, this paper introduces how to select suitable 2D and 3D optical imaging technology according to the optical characteristics of the test object. Secondly, the important functions of image denoising, feature extraction, image segmentation and image Mosaic are introduced. Then, according to the implementation principle of defect detector, it is divided into five categories: Template matching, image classification, image semantic segmentation, target detection and image anomaly detection, and the classical algorithms are summarized and analyzed. Finally, this paper discusses the key problems in the implementation of surface defect detection in the industrial scene, and looks forward to the development trend of this technology.