2006 SICE-ICASE International Joint Conference 2006
DOI: 10.1109/sice.2006.314680
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Development of Real-time Defect Detection Algorithm for High-speed Steel Bar in Coil(BIC)

Abstract: In steel manufacturing industry, as many advanced technologies increase manufacturing speed, fast and exact products inspection gets more important. This paper deals with a real-time defect detection algorithm for high-speed steel bar in coil (BIC). To get good performance, this algorithm has to solve several difficult problems such as cylindrical shape of a BIC, influence of light, many kinds of defects. Additionally, it should process quickly the large volumes of image for real-time processing since a steel … Show more

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Cited by 15 publications
(10 citation statements)
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References 11 publications
(5 reference statements)
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“…Nor is it necessary to ensure the regularity of the surface that is imaged, relaxing the photometric stereo constraints, and adopting a lighter version of the shape from shading problem. Other state-of-the-art computer vision solutions essentially focus on differences between brute-force and pixel-wise, or, in case of more refined but computationally expensive techniques, edge extraction [2] or wavelet operators [3]. None of these methods are immune to a significant amount of false positives and false negatives, which translates into false alarms and unseen defects, mostly due to sensor noise, hardware misalignments, bad illumination conditions and other external factors that affect the images.…”
Section: Optical Inspectionmentioning
confidence: 99%
“…Nor is it necessary to ensure the regularity of the surface that is imaged, relaxing the photometric stereo constraints, and adopting a lighter version of the shape from shading problem. Other state-of-the-art computer vision solutions essentially focus on differences between brute-force and pixel-wise, or, in case of more refined but computationally expensive techniques, edge extraction [2] or wavelet operators [3]. None of these methods are immune to a significant amount of false positives and false negatives, which translates into false alarms and unseen defects, mostly due to sensor noise, hardware misalignments, bad illumination conditions and other external factors that affect the images.…”
Section: Optical Inspectionmentioning
confidence: 99%
“…So far a great deal of research has been made in automatic detection of defects available on the surface of steel sheets [1], [2]. Among other approaches used for locating the defects, we can name laplace filter, gradient filter, and RAF filter [3], [4]. Application of these filters on images makes the defective edges and unimportant details of the screen to be exposed with the same intensity.…”
Section: Introductionmentioning
confidence: 99%
“…[1][2][3] To meet this demand, new sensors are needed to measure exact information about the objects and new algorithms are required to obtain, exactly, the desired value from the measured data. The development of new robust systems to detect the defects in products of the steel process is one of the ways to improve quality and productivity.…”
Section: Introductionmentioning
confidence: 99%