摘要
针对传统型材表面缺陷检测存在测量精度低、稳定性差和费时等问题,提出了基于机器视觉的型材表面缺陷图像处理方法。为了提高型材表面缺陷检测的精度和效率,采用面阵相机、镜头和光源等,建立了基于机器视觉的型材表面缺陷检测系统。采用HALCON图像处理软件对获取的型材图像进行预处理、灰度值调整、形态学操作和提取缺陷特征。试验结果表明:文中所提出的型材表面缺陷图像处理方法可快速、准确识别缺陷特征,为型材表面缺陷检测提供了一种方法。
Aiming at the problems of low measurement accuracy,poor stability and time-consuming in traditional profile surface defect detection,a method of section steel surface defect image processing based on machine vision is proposed.In order to improve the accuracy and efficiency of section steel surface defect detection,a profile surface defect detection system based on machine vision is established by using area array camera,lens and light source.HALCON image processing software is used to preprocess the profile image,adjust the gray value,operate morphology and extract defect features.The experimental results show that the image processing method proposed in this paper can identify the defect features quickly and accurately,and provide a method for the detection of section steel surface defects.
作者
郑彬
王鑫
ZHENG Bin;WANG Xin(School of Transportation and Automobile Engineering,Panzhihua University,Panzhihua 617000)
出处
《机械设计》
CSCD
北大核心
2020年第S01期95-97,共3页
Journal of Machine Design
基金
攀枝花市指导性科技计划资助项目(2019ZD-N-2)
关键词
型材
机器视觉
表面缺陷
图像处理
section steel
machine vision
surface defect
image processing
作者简介
郑彬(1979—),男,高级工程师/副教授,硕士生导师,博士,研究方向:发动机零部件结构设计及优化。E-mail:22198334@qq.com
