计算机与数字工程2024，Vol.52Issue(4)：1221-1227,7.DOI:10.3969/j.issn.1672-9722.2024.04.047
基于机器视觉的雨刮器表面缺陷检测
Surface Defects Detection of Wipers Based on Machine Vision
谢丹 1贺福强 1何昊 1纪家平1
作者信息
- 1. 贵州大学机械工程学院 贵阳 550025
- 折叠
摘要
Abstract
Aiming at the common typical surface defects of wiper,such as scratches,spots(pits and sand holes),a method of wiper surface defect detection based on machine vision is proposed.Firstly,according to the surface image of the wiper collected by CCD,the image morphology processing and Gabor filtering method are used to suppress the texture noise of the metal frosting by designing specific structural elements of image preprocessing,and the gamma gray image enhancement algorithm is used to enhance the contrast between the wiper defect and the background.Then,the image maximum entropy threshold defect is used to segment the surface defects of the wiper.Finally,the feature extraction and classification of typical defects on the surface of the metal wiper shell are realized,and the size of the relevant defects is calculated.The experimental results show that the detection speed of the pro-posed method for typical surface defects of wiper in industrial production reaches an average of 0.724 s/piece,which has good detec-tion accuracy and can be well adapted to the industrial environment.关键词
雨刮器/形态学/Gabor滤波器/机器视觉/缺陷检测Key words
wiper/morphology/Gabor filter/machine vision/defects detection分类
机械制造引用本文复制引用
谢丹,贺福强,何昊,纪家平..基于机器视觉的雨刮器表面缺陷检测[J].计算机与数字工程,2024,52(4):1221-1227,7.
