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The 2- and 3-point surface correlation functions calculations: From novel exact continuous approach to improving methodology for discrete images

Author

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  • Postnicov, Vasily
  • Karsanina, Marina V.
  • Khlyupin, Aleksey
  • Gerke, Kirill M.

Abstract

Surface correlation functions are extremely useful descriptors of interfaces and in this role can be used in material science, rock and soil physics, food engineering and other numerous areas. However, their widespread usage was hampered by insufficiently robust computation methodologies. In this contribution we elaborate on recent works in surface function evaluation and present a novel exact algorithm to compute surface–surface (Fss) and surface–surface–surface (Fsss) functions for smooth boundary sets without discretization. This allows us to test digital computational approach on geometries beyond those available as analytical solutions. Moreover, we propose a better edge detection filter that allowed to improve the quality of assessment of surface correlation functions, both surface–surface (Fss) and surface-void (Fsv), for digital images. The code for continuous and discrete computational frameworks is freely available and is now the part of the more general CorrelationFunctions.jl package.

Suggested Citation

  • Postnicov, Vasily & Karsanina, Marina V. & Khlyupin, Aleksey & Gerke, Kirill M., 2023. "The 2- and 3-point surface correlation functions calculations: From novel exact continuous approach to improving methodology for discrete images," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    • Handle: RePEc:eee:phsmap:v:628:y:2023:i:c:s0378437123006921
    DOI: 10.1016/j.physa.2023.129137
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    References listed on IDEAS

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    1. Marina V Karsanina & Kirill M Gerke & Elena B Skvortsova & Dirk Mallants, 2015. "Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-26, May.
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    Cited by:

    1. Cherkasov, Aleksei & Gerke, Kirill M. & Khlyupin, Aleksey, 2024. "Towards effective information content assessment: Analytical derivation of information loss in the reconstruction of random fields with model uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).

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