Quantitative evaluation of surface roughness of flat metal surfaces using computer vision system

被引:0
作者
Inamdar, Kedar H. [1 ]
Joshi, S. G. [1 ]
机构
[1] Walchand Coll Engn, Dept Mech Engn, Sangil 416415, Maharashtra, India
来源
Proceedings of the 8th Biennial Conference on Engineering Systems Design and Analysis, Vol 4 | 2006年
关键词
surface roughness; computer vision system; RGB colour cube model; multiple regression;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this paper, a method of quantitative evaluation of surface roughness based on computer vision system is presented. A low cost computer vision system consisting of flat bed desktop scanner connected to personal computer (PC) is used. A large number of surface specimens such as EN-8, EN-9, cast iron, copper, brass, aluminium, C-20, C-45 steel etc. were carefully prepared by using various machining processes like planing, shaping, turning, milling, grinding, polishing etc. to generate a database of surface specimens with different lay-types and surface roughness values. This database is evaluated for conventional surface roughness parameters like R-t, R-a, R-q and for RGB colour component values at each pixel over the digital images of these produced surfaces. By using the technique of multiple linear regression analysis, the conventional roughness values and colur component values were correlated with each other to form a multiple linear regression equation for R,. The value of surface roughness R, obtained for a given specimen using this equation was then crosschecked and confirmed with the results obtained by using conventional method for the same specimen. When any test surface is introduced for surface roughness evaluation, the developed method relates the colour component values obtained from its surface image, to the conventional values like Rt, R,, Rq, In addition to this, surface topographical representation and summits are also presented. Using this method even the evaluation of the surface roughness in the nano-mctre level can be carried out to fulfill the requirements of experimental field of 0.001 to 50 microns.
引用
收藏
页码:743 / 749
页数:7
相关论文
共 4 条
[1]  
INAMDAR KH, 2005, J CENTRAL MANUFACTUR, V4, P11
[2]  
INAMDAR KH, 2005, J CENTRAL MANUFACTUR, V4, P17
[3]  
Rafel CG., 2002, DIGITAL IMAGE PROCES
[4]  
Sonka Milan, 1998, Image Processing, Analysis and Machine Vision