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Allocation of perlite grains on metallographic images of low-carbon steel

Keywords:

R.G. Magdeev – Leading Engineer, «Telekom.ru» LLC (Ulyanovsk)
E-mail: radiktkd2@yandex.ru
A.G. Tashlinsky – Dr.Sc.(Eng.), Professor, Head of Department «Radio Engineering», Ulyanovsk State Technical University
E-mail: tag@ulstu.ru


One of the important tasks in the manufacturing and usage of steel products is to control their compliance with the required charac-teristics (mechanical properties, residual resource, etc.). All microstructures of low-carbon and low-alloy steels contain a perlite-eutectoid mechanical mixture of ferrite and cementite. A peculiarity of the microstructure of steel is the presence of internal boundaries separating the perlite grains in the metal. Numerous studies have shown the relationship between the parameters of the microstructure and the mechanical properties of metals and alloys. Therefore, the development of a technique that allows to automate of the process of determining microstructural characteristics on the basis of methods and algorithms for processing digital images is relevant. An important task in this case is the automated allocation of perlite grains on metallurgical images and the determination of their characteristics by which the microstructural parameters of the steel can be found. The paper considers one of the approaches to solving this problem which uses the procedures for segmenting the areas of perlite on the image, their morphological processing, the isolation of individual grains, finding their boundaries and convex hulls.
The stage of segmentation of the perlite regions, aimed at isolating the areas of the location of pearlite grains, is done using binarization of the image on the basis of histogram analysis. The operations of mathematical morphology are aimed at eliminating internal discontinuities in the images of grains and excluding from the further analysis of small clusters of perlite. To isolate the areas of location of individual grains the method of growing areas is used. The outer boundaries of the grains are found using the recursive bug algorithm, which belongs to the class of algorithms for the sequential construction of contours. For the construction of convex hulls of grains, the quick-build algorithm (QuickHull) based on the Hoare sorting principle was chosen, which showed a minimum of errors for the problem being solved and makes it possible to parallelize the computations.
After the selection of the convex hulls of the perlite grains, the areas and lengths of the perimeter of the spot and the convex hull and other geometric characteristics are calculated, which are then used to estimate such microstructural parameters as the number of perlite grains in the image, the perlite-to-ferrite ratio, perlite grain, the general grain orientation vector, the average grain size, the spread of grain sizes, the degree of ordering of the grain orientations and the average value of the anisotropic form factor.

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