A technique for determining the parameter values from experimental images for the porous structures generator for synthesizing porous phantoms is presented. The algorithms for fast determination of porosity and the standard deviation of the Gaussian filter used as input parameters of the phantom generator are considered. The phantoms generated according to the found parameters have geometric characteristics similar to the original images, which makes it possible to use such phantoms both for studying and modeling processes in porous media and as basic structures for creating training samples for segmentation algorithms of experimental images using machine learning methods..
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