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Applied Optics

Applied Optics


  • Editor: Joseph N. Mait
  • Vol. 50, Iss. 26 — Sep. 10, 2011
  • pp: 5122–5129

Pinhole detection in steel slab images using Gabor filter and morphological features

Doo-chul Choi, Yong-ju Jeon, Jong Pil Yun, and Sang Woo Kim  »View Author Affiliations

Applied Optics, Vol. 50, Issue 26, pp. 5122-5129 (2011)

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Presently, product inspection for quality control is becoming an important part in the steel manufacturing industry. In this paper, we propose a vision-based method for detection of pinholes in the surface of scarfed slabs. The pinhole is a very tiny defect that is 1– 5 mm in diameter. Because the brightness in the surface of a scarfed slab is not uniform and the size of a pinhole is small, it is difficult to detect pinholes. To overcome the above-mentioned difficulties, we propose a new defect detection algorithm using a Gabor filter and morphological features. The Gabor filter was used to extract defective candidates. The morphological features are used to identify the pinholes among the defective candidates. Finally, the experimental results show that the proposed algorithm is effective to detect pinholes in the surface of the scarfed slab.

© 2011 Optical Society of America

OCIS Codes
(150.0150) Machine vision : Machine vision
(150.1135) Machine vision : Algorithms

ToC Category:
Machine Vision

Original Manuscript: February 17, 2011
Revised Manuscript: July 24, 2011
Manuscript Accepted: August 2, 2011
Published: September 8, 2011

Doo-chul Choi, Yong-ju Jeon, Jong Pil Yun, and Sang Woo Kim, "Pinhole detection in steel slab images using Gabor filter and morphological features," Appl. Opt. 50, 5122-5129 (2011)

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