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http://dx.doi.org/10.5302/J.ICROS.2013.12.1849

Classifying Scratch Defects on Billets Using Image Processing and SVM  

Lee, Sang Jun (POSTECH)
Kim, Sang Woo (POSTECH)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.19, no.3, 2013 , pp. 256-261 More about this Journal
Abstract
In the steel manufacturing area, researches for defect inspection receive a big attention for quality control. This paper proposes an algorithm to detect a scratch defect on steel billets. This algorithm takes ROIs (Regions of Interest), and extracts 11 features which represent properties of defect on a ROI. SVM (Support Vector Machine) is used to classify defect and normal ROIs. The algorithm classifies a frame image of a Billet as a defect image if there is one or more defect ROIs. In the experiments, the proposed algorithm had reliable classifying accuracy.
Keywords
steel; defect detection; automation; inspection system; image analysis;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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