基于计算机视觉的工业金属表面缺陷检测综述  

A Review of Metal Surface Defect Detection Based on Computer Vision

作　　者：伍麟 郝鸿宇 宋友[1] WU Lin;HAO Hong-Yu;SONG You(School of Software,Beihang University,Beijing 100191)

机构地区：[1]北京航空航天大学软件学院,北京100191

出　　处：《自动化学报》2024年第7期1261-1283,共23页Acta Automatica Sinica

摘　　要：针对平面及三维结构金属材料的工业表面缺陷检测,概述了视觉检测技术的基本原理和研究现状,并总结出视觉自动检测系统的关键技术包括光学成像技术、图像预处理技术与缺陷检测器.首先介绍了如何根据检测对象的光学特性选择合适的二维、三维光学成像技术;其次介绍了图像降噪、特征提取、图像分割和拼接等预处理技术的重要作用;然后根据缺陷检测器的实现原理将其分为模板匹配、图像分类、图像语义分割、目标检测和图像异常检测五类,并对其中的经典算法进行了归纳分析.最后,探讨了工业场景下金属表面缺陷检测技术实施中的关键问题,并对该技术的发展趋势进行了展望.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.

关 键 词：表面缺陷检测 计算机视觉 金属表面缺陷 自动化检测 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TG115[自动化与计算机技术—计算机科学与技术]