摘要
将机器视觉引入电镀件表面缺陷检测中,设计了一种基于机器视觉的电镀件表面缺陷检测系统。该系统由工控机、图像采集卡、工业相机、伺服电机、照明装置和运动控制卡组成。获取电镀件表面光学图像并经预处理后,利用算法提取出图像中缺陷区域边界特征,通过计算用于标记缺陷区域边界特征的白色像素点个数,并与设定的阈值做比较,实现电镀件表面缺陷检测。该系统满足电镀件表面缺陷在线检测的要求。
Computer vision was applied to detection of the surface defects of electroplated parts,and a surface defects detection system for electroplated parts based on computer vision was designed.This system was composed of industrial personal computer,image capture card,industrial camera,servo motor,lighting device and motion control card.The surface optical image of electroplated parts was obtained,and after the pre-processing,the boundary characteristics of defect area in the image was extracted and the number of white pixels for labeling the boundary characteristics of defect area was calculated.Comparing the calculated value with the predetermined threshold,then to realize the detection of the surface defects of electroplated parts.This system can meet the requirements of online detection of surface defects of electroplated parts.
作者
卢颖颖
孙育
LU Yingying;SUN Yu(Nanyang Radio and TV University,Nanyang 473000,China;Zhengzhou Institute of Finance and Economics,Zhengzhou 450044,China)
出处
《电镀与环保》
CAS
CSCD
北大核心
2019年第2期59-61,共3页
Electroplating & Pollution Control
基金
河南省科技攻关重点计划项目(132102210215)
关键词
检测系统
电镀件表面缺陷
机器视觉
图像预处理
特征提取
detection system
surface defects of electroplated parts
computer vision
image pre-processing
feature extraction
