Image recognition of shape defects in hot steel rolling

E. Balmashnova, L.C.M. Bruurmijn, R. Dissanayake, R. Duits, L. Kampmeijer, T.L. Noorden, van

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A frequently occurring issue in hot rolling of steel is so-called tail pinching. Prominent features of a pinched tail are ripple-like defects and a pointed tail. In this report two algorithms are presented to detect those features accurately in 2D gray scale images of steel strips. The two ripple detectors are based on the second order Gaussian derivative and the Gabor transform, a localized Fourier transform, yielding the so-called rippleness measures. Additionally a parameter called tail length is defined which indicates to what extent the overall shape of the tail deviates from an ideal rectangular shape. These methods are tested on images from the surface inspection system at Tata Hot Strip Mill 2 in IJmuiden, it is shown that by defining a simple criterion in the feature space spanned by these two parameters a given set of strips can correctly be classified into pinched and nonpinched strips. These promising results open the way for the development of an automatic pinch detection system.
Original languageEnglish
Title of host publicationProceedings of the 84th European Study Group Mathematics with Industry (SWI 2012)
EditorsM.A.A. Boon
Publication statusPublished - 2013
Event84th European Study Group Mathematics with Industry (SWI 2012) - Eindhoven, Netherlands
Duration: 30 Jan 20123 Feb 2012


Conference84th European Study Group Mathematics with Industry (SWI 2012)
Abbreviated titleSWI 2012
Internet address


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