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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*
  • *Corresponding author for this work
  • Korea Institute of Industrial Technology
  • Pohang University of Science and Technology
  • POSCO

Research output: Contribution to journalJournal articlepeer-review

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.

Original languageEnglish
Article number053108
JournalOptical Engineering
Volume56
Issue number5
DOIs
StatePublished - 2017

Keywords

  • defect detection
  • machine vision
  • steel surface
  • surface inspection

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