Using MAZA Library to Process Soil and Other Porous Media XCT Images

This work closes the gap and eliminates the problem of availability of correct state-of-the-art local thresholding algorithms for X-ray tomography image segmentation. We provide a free library with graphical user interface that implements all major binarization algorithms—indicator kriging, region growing, converging active contours and Markov random field methods. MAZA library (MAjor binariZAtion library) also provides filters for image pre-processing. In addition, we explored and reported the sensitivity of the parameters of the segmentation methods and their computational complexity in terms of CPU time. There was not a clear winner among implemented segmentation algorithms and one needs to choose an approach depending on the X-ray image at hand and its quality.

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Publication Details

Journal
Eurasian Soil Science
Published
2026-02-23
DOI
https://doi.org/10.1134/s1064229325603130
Primary Topic
Microbial Applications in Construction Materials
Type
article
Field-Weighted Citation Impact
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article

Using MAZA Library to Process Soil and Other Porous Media XCT Images

A. A. Ananev, M. V. Karsanina, K. D. Tolstygin, M. Gravey et al.
Eurasian Soil Science
Microbial Applications in Construction Materials
article

Using MAZA Library to Process Soil and Other Porous Media XCT Images

A. A. Ananev, M. V. Karsanina, K. D. Tolstygin, M. Gravey, A. M. Cherkasov, A.N. Khlyupin, K. N. Abrosimov, K. M. Gerke, R. V. Vasilyev
article en

Abstract

This work closes the gap and eliminates the problem of availability of correct state-of-the-art local thresholding algorithms for X-ray tomography image segmentation. We provide a free library with graphical user interface that implements all major binarization algorithms—indicator kriging, region growing, converging active contours and Markov random field methods. MAZA library (MAjor binariZAtion library) also provides filters for image pre-processing. In addition, we explored and reported the sensitivity of the parameters of the segmentation methods and their computational complexity in terms of CPU time. There was not a clear winner among implemented segmentation algorithms and one needs to choose an approach depending on the X-ray image at hand and its quality.

Eurasian Soil ScienceVol. 59(3)
Moscow Institute of Physics and Technology (RU), Institute for Interdisciplinary Mountain Research (AT), Schmidt Institute of Physics of the Earth (RU), V.V. Dokuchaev Soil Science Institute (RU)
Openalex Percentile: Top 54%
Microbial Applications in Construction Materials
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