Measurement of surface roughness by a machine vision system

1989 ◽  
Vol 22 (12) ◽  
pp. 977-980 ◽  
Author(s):  
F Luk ◽  
V Huynh ◽  
W North
Author(s):  
Richard Y. Chiou ◽  
Yongjin James Kwon ◽  
Yueh-Ting Yang ◽  
Robin Kizirian ◽  
Tzu-Liang Bill Tseng

This paper presents a new method of surface roughness measurement developed for use in a web-enabled production environment. This method employs an Internet-based vision system to measure and analyze the pattern of scattered light from a surface of an object to derive roughness parameters. The roughness parameters are obtained for a number of metal specimens which are machined to different roughnesses. A correlation curve is established between optical intensity and the corresponding average surface roughness. The quality measurement data is monitored through the web browser while surface roughness parameters are inspected using a machine vision system. This allows the system to operate over the Internet since the machine vision system is integrated with LabVIEW-based graphic user interface (GUI).


Fast track article for IS&T International Symposium on Electronic Imaging 2020: Stereoscopic Displays and Applications proceedings.


2005 ◽  
Vol 56 (8-9) ◽  
pp. 831-842 ◽  
Author(s):  
Monica Carfagni ◽  
Rocco Furferi ◽  
Lapo Governi

2012 ◽  
Vol 546-547 ◽  
pp. 1382-1386
Author(s):  
Yin Xia Liu ◽  
Ping Zhou

In order to promote the application and development of machine vision, The paper introduces the components of a machine vision system、common lighting technique and machine vision process. And the key technical problems are also briefly discussed in the application. A reference idea for application program of testing the quality of the machine parts is offered.


Mechatronics ◽  
2006 ◽  
Vol 16 (5) ◽  
pp. 243-247 ◽  
Author(s):  
Zhenwei Su ◽  
Gui Yun Tian ◽  
Chunhua Gao

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