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Optical Engineering

Vision-based defect detection of scale-covered steel billet surfaces
Author(s): Jong Pil Yun; SungHoo Choi; Sang Woo Kim
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Paper Abstract

Vision-based inspection systems have been widely investigated for the detection and classification of defects in various industrial product. We present a new defect detection algorithm for scale-covered steel billet surfaces. Because of the availability of various kinds of steel, presence of scales, and manufacturing conditions, the features of billet surface images are not uniform. In particular, scales severely change the properties of defect-free surfaces. Moreover, the various kinds of possible defects make their detection difficult. In order to resolve these problems and to improve the detection performance, two methods are proposed. First, undecimated wavelet transform and vertical projection profile are presented. Second, a method for detecting the variations in the block features along the vertical direction is proposed. The former method can effectively detect vertical line defects, and the latter can efficiently detect the remaining defects, except the vertical line defects. The experimental results conducted on billet surface images obtained from actual steel production lines show that the proposed algorithm is effective for defect detection of scale-covered steel billet surfaces.

Paper Details

Date Published: 1 March 2009
PDF: 9 pages
Opt. Eng. 48(3) 037205 doi: 10.1117/1.3102066
Published in: Optical Engineering Volume 48, Issue 3
Show Author Affiliations
Jong Pil Yun, Pohang Univ. of Science and Technology (Korea, Republic of)
SungHoo Choi, Pohang Univ. of Science and Technology (Korea, Republic of)
Sang Woo Kim, Pohang Univ. of Science and Technology (Korea, Republic of)

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