JOURNAL BROWSE
Search
Advanced SearchSearch Tips
A Micro-defect Detection of Cold Rolled Steel
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Micro-defect Detection of Cold Rolled Steel
Yun, Jong Pil;
 
 Abstract
In this paper, we propose a new defect detection technology for micro-defect on the surface of steel products. Due to depth and size of microscopic defect, slop of surface and vibration of strip, the conventional optical method cannot guarantee the detection performance. To solve the above-mentioned problems and increase signal to noise ratio, a novel retro-schlieren method that consists of retro reflector and knife edge is proposed. Moreover dual switching lighting method is also applied to distinguish uneven micro defects and surface noise. In proposed method, defective regions are represented by a black and white pattern. This pattern is detected by a defect detection algorithm with Gabor filter. Experimental results by simulator for sample defects of cold rolled steel show that the proposed method is effective.
 Keywords
defect detection;machine vision;image processing;steel surface;
 Language
Korean
 Cited by
 References
1.
A. Kumar, "Computer-vision-based fabric defect detection: A survey," IEEE Transactions on Industrial Electronics, vol. 55, no. 1, pp. 348-363, Jan. 2008.

2.
C. S. Cho, B. M. Chung, and M. J. Park, "Development of real-time vision-based fabric inspection system," IEEE Transactions on Industrial Electronics, vol. 52, no. 4, pp. 1073-1079, Aug. 2005.

3.
J. H. Oh, B. J. Yun, S. Y. Kim, and K. H. Park, "A development of the TFT-LCD image defect inspection method based on human visual system," IEICE Transactions on Fundamentals, vol. E91-A, no. 6, pp. 1400-1407, Jun. 2008. crossref(new window)

4.
L. M. Sanchez-Brea, P. Siegmann, M. A. Rebollo, and E. Bernabeu, "Optical technique for the automatic detection and measurement of surface defects on thin metallic wires," Applied Optics, vol. 39, no. 4, pp. 539-545, Feb. 2000. crossref(new window)

5.
Z. Wen and Y. Tao, "Brightness-invariant image segmentation for on-line fruit defect detection," Optical Engineering, vol. 37, no. 11, pp. 2948-2952, Nov. 1998. crossref(new window)

6.
J. P. Yun, Y. J. Jeon, D. C. Choi, and S. W. Kim, "Real-time defect detection of steel wire rods using wavelet filters optimized by univariate dynamic encoding algorithm for searches (uDEAS)," Journal of the Optical Society of America A, vol. 29, no. 5, pp. 797-807, May 2012. crossref(new window)

7.
D. C. Choi, Y. J. Jeon, and S. W. Kim, "Faulty scarfing slab detection using machine vision," Advanced Materials Research, vol. 462, pp. 185-190, Feb. 2012. crossref(new window)

8.
Y. J. Jeon, D. C. Choi, J. P. Yun, and S. W. Kim, "Detection of periodic defects using dual-light switching lighting method on the surface of thick plates," ISIJ International, vol. 55, no. 9, pp. 1942-1949, Sep. 2015. crossref(new window)

9.
Y. J. Jang and J. S. Lee, "Development of a 3D shape reconstruction system for defects on a hot steel surface," Journal of Institute of Control Robotics and Systems, vol. 21, no. 5, pp. 459-464, 2015.

10.
J. P. Yun, C. H. Park, H. M. Bae, S. H. Choi, and J. H. Yun, "Micro defect detection of cold rolled steel using dual retro-schlieren technology," Proc. of 2014 29th ICROS Annual Conference (in Korean), Daegu, Korea, pp. 370-371, May 2014. pp. 370-371, 2014.