Analysis of Steel Bar Surface Defects Based on Machine Vision

Wu Bin Li; Chang Hou Lu; Jian Chuan Zhang

doi:10.4028/www.scientific.net/AMR.549.1017

Paper Titles

Flotation to Recover Copper Minerals from a Low-Grade Copper-Bearing Iron Ore
p.998

Study and Application on Cutting Technology of Underground Drifting Blasting
p.1002

Detection of Weld Seam Position Based on Infrared Image during High Power Fiber Laser Welding
p.1007

Data Process for Reverse Engineering Technology
p.1012

Analysis of Steel Bar Surface Defects Based on Machine Vision
p.1017

The Development Mode of Mechanical and Electrical Products 3D Part Library
p.1021

Research of Product Design Evaluation Based on Informational Engineering Models
p.1026

Application of Low-Position Vacuum Deaerator in Steam Injection Boiler Supply Water Deaeration in Oil Fields
p.1032

Study on Laser Ignition Characteristics of NEPE Propellant
p.1037

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 549Analysis of Steel Bar Surface Defects Based on...

Analysis of Steel Bar Surface Defects Based on Machine Vision

Abstract:

In order to guarantee the steel bar quality, we describe the category of steel bar surface defects in details. Generally, there are about two main categories of steel bar surface defects which include linear and area-like defects. Secondly, the characteristics of the steel bar surface image are analyzed at large. Both of them support a foundation for the future inspection of steel bar surface quality.

You might also be interested in these eBooks

Chemical Engineering and Material Properties II

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 549)

Pages:

1017-1020

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.549.1017

Citation:

Cite this paper

Online since:

July 2012

Authors:

Wu Bin Li, Chang Hou Lu, Jian Chuan Zhang

Keywords:

Defect Detection, Image Analysis, Machine Vision, Surface Defect

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] W.B. Li, C.H. Lu, J.C. Zhang. Advanced Materials Research. Vol. 308-310 (2011), p.1328.

Google Scholar

[2] P.H. Chen, H.K. Shen, C.Y. Lei, L.M. Chang. Procedia Engineering, Vol. 14 (2011), p.470.

Google Scholar

[3] W.B. Li, C.H. Lu, J.C. Zhang. Applied Surface Science. Vol. 258 (2012), p.6080.

Google Scholar

[4] Y. Sun, P. Bai, H.Y. Sun, P. Zhou. NDT & E International. Vol. 38 (2005), p.522.

Google Scholar

[5] T. Shinohara, K. Yoshida. Journal of Materials Processing Technology. Vol. 162–163 (2005), p.579.

Google Scholar

[6] I.H. Son, J.D. Lee, S. Choi, D.L. Lee, Y.T. Im. Journal of materials processing technology. Vol. 201 (2008), p.91.

Google Scholar

[7] M. Awais, H.W. Lee, Y.T. Im, H.C. Kwon, S.M. Byon, H.D. Park. Journal of materials processing technology. Vol. 201 (2008), p.73.

Google Scholar

[8] H.Y. Kim, H.C. Kwon, H.W. Lee, Y.T. Im, S.M. Byon, H.D. Park. Journal of materials processing technology. Vol. 205 (2008), p.70.

Google Scholar

[9] H.C. Kwon, H.W. Lee, H.Y. Kim, Y.T. Im, H.D. Park, D.L. Lee. Journal of Materials Processing Technology. Vol. 209 (2009), p.4476.

Google Scholar

[10] K. Agarwal, R. Shivpuri, Y.J. Zhu, T.S. Chang, H. Huang. Expert Systems with Applications. Vol. 38 (2011), p.7251.

Google Scholar