1 March 2009 Vision-based defect detection of scale-covered steel billet surfaces
Jong Pil Yun, SungHoo Choi, Sang Woo Kim
Author Affiliations +
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.
©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)
Jong Pil Yun, SungHoo Choi, and Sang Woo Kim "Vision-based defect detection of scale-covered steel billet surfaces," Optical Engineering 48(3), 037205 (1 March 2009). https://doi.org/10.1117/1.3102066
Published: 1 March 2009
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CITATIONS
Cited by 41 scholarly publications.
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KEYWORDS
Defect detection

Detection and tracking algorithms

Inspection

Wavelet transforms

Image segmentation

Linear filtering

Wavelets

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