Method for identification of perlite-class steel microstructure parameters using metallographic images

A method for finding the microstructural parameters of low-carbon steel using its metallographic images is proposed. It allows to determine the following parameters: the ratio of perlite to ferrite phases, the parameters of grains of crystallites and their mutual arrangement; the degree of granularity of the pearlite phases. The method is aimed at predicting the strength characteristics of steel samples and consists of several stages. The preprocessing step involves color reduction, refinement of the area of interest, noise filtering, illumination refinement and histogram equalization. The segmentation of the image is associated with the search for the size, area and convex shell of grains. The stage of finding the microstructural parameters is based on the stochastic gradient-based estimation of the parameters of the segmented objects. Examples of analysis of steel oil pipeline samples with a forecast of their strength characteristics are given.