scholarly journals Research on steel ball surface defect detection device based on machine vision

2021 ◽  
Vol 2029 (1) ◽  
pp. 012127
Author(s):  
Chenchen Dong ◽  
Weiwei Zhu ◽  
Jinling Wei ◽  
Hangchao Zhou ◽  
Feng Chen
2011 ◽  
Vol 403-408 ◽  
pp. 1356-1359
Author(s):  
Fu Juan Wang ◽  
Yong Qiang Dong

In order to implement the accuracy and robust of Chinese dates surface defect detection based on machine vision techniques on line, the method of detection for Chinese dates was studied. The Chinese date is segmented from the background in RGB color space by analyzing respectively the histogram of R, G and B channel to make comparing among them and find an optimal one, resulting in good contrast between Chinese date and background in G channel. The brightness of the damaged area edge changed clearly on the whole Chinese dates area according to the gray image of R, G and B channel, especially in G channel. It shows the gray value of the defect area breaking obviously. So the damaged area could be detected by edge detect, through image thinning the defect edge was extracted. Furthermore, the geometry parameters of defect edge were calculated, these parameters could used to distinguish the defect area with the fruit area and the degree of the defect area. Experiments result proved the methods is effective to detect defect area of Chinese date.


2021 ◽  
Author(s):  
Yiwen Wang ◽  
Kaijiao Wang ◽  
Lijie Zhou ◽  
Yun Chen ◽  
Pengfei Li

2011 ◽  
Vol 295-297 ◽  
pp. 1274-1278 ◽  
Author(s):  
Jian Xi Yang ◽  
Fa Yu Zhang ◽  
Xiao Xia Song ◽  
Hong Zhe Xu

According to requirements of online steel ball surface defect inspection, the automatic detection method of spherical surface defect on the track has been posed. To ensure photographing of the whole steel ball surface, the six CCD video cameras are used in this system. To overcome steel ball surface reflection, the red LED light source is used, and then the real and clear images are got. The steel ball surface defect is recognized accurately by means of image recognition technology and image reconstruction technology etc. This method provides theoretical basis and technical support for ball defection and quality classification.


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