Vision-based surface defect inspection for thick steel plates

Jong Pil Yun; Dongseob Kim; KyuHwan Kim; Sang Jun Lee; Chang Hyun Park; Sang Woo Kim

doi:10.1117/1.OE.56.5.053108

22 May 2017 Vision-based surface defect inspection for thick steel plates

Jong Pil Yun, Dongseob Kim, KyuHwan Kim, Sang Jun Lee, Chang Hyun Park, Sang Woo Kim

Author Affiliations +

Optical Engineering, Vol. 56, Issue 5, 053108 (May 2017). https://doi.org/10.1117/1.OE.56.5.053108

Abstract

There are several types of steel products, such as wire rods, cold-rolled coils, hot-rolled coils, thick plates, and electrical sheets. Surface stains on cold-rolled coils are considered defects. However, surface stains on thick plates are not considered defects. A conventional optical structure is composed of a camera and lighting module. A defect inspection system that uses a dual lighting structure to distinguish uneven defects and color changes by surface noise is proposed. In addition, an image processing algorithm that can be used to detect defects is presented in this paper. The algorithm consists of a Gabor filter that detects the switching pattern and employs the binarization method to extract the shape of the defect. The optics module and detection algorithm optimized using a simulator were installed at a real plant, and the experimental results conducted on thick steel plate images obtained from the steel production line show the effectiveness of the proposed method.

Citation Download Citation

Jong Pil Yun, Dongseob Kim, KyuHwan Kim, Sang Jun Lee, Chang Hyun Park, and Sang Woo Kim "Vision-based surface defect inspection for thick steel plates," Optical Engineering 56(5), 053108 (22 May 2017). https://doi.org/10.1117/1.OE.56.5.053108

Received: 10 November 2016; Accepted: 26 April 2017; Published: 22 May 2017

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