摘要
基于机器视觉技术对板材表面缺陷检测进行研究,设计了在线检测的硬件系统和软件处理流程,介绍了图像预处理、图像分割和目标提取等处理方法并对缺陷图像进行相应处理。利用C#软件对板材缺陷在线检测进行人机交互界面设计和在线调试及在线检测。实验结果表明,本检测方法可行,误检率低,可很好地应用于木材自动化生产过程的在线检测。
This paper presents a study into board surface defect detection based on machine vision technology.On-line detection hardware system and software processing procedure were designed in the study. This paper also described image preprocessing, image segmentation, and object extraction techniques and covered appropriate processing of defect images. C# software was utilized to develop MMI interfaces for on-line board surface defect detection. On- line debugging and on- line detection were carried out. It has been proven by experimentation that this detection approach was feasible and registered a low error detection rate, and may be thus used with advantage in on-line detection during automatic wood production process.
出处
《莆田学院学报》
2016年第5期43-47,共5页
Journal of putian University
基金
福建省科技厅区域重大基金项目(2015H4009)
莆田市科技计划基金项目(2014G15)
关键词
机器视觉
表面缺陷
在线检测
数字图像处理
computer vision
surface defection
on-line detection
digital image processing