pytrax: A simple and efficient random walk implementation for calculating the directional tortuosity of images

Given the huge advances in tomographic imaging capability in recent years, image analysis has become a powerful means of measuring transport and structural properties of porous materials. One of the most important material characteristics is the tortuosity, which is difficult to measure experimental...

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Bibliographic Details
Main Authors: T.G. Tranter, M.D.R. Kok, M. Lam, J.T. Gostick
Format: Article
Language:English
Published: Elsevier 2019-07-01
Series:SoftwareX
Online Access:http://www.sciencedirect.com/science/article/pii/S2352711019302286
Description
Summary:Given the huge advances in tomographic imaging capability in recent years, image analysis has become a powerful means of measuring transport and structural properties of porous materials. One of the most important material characteristics is the tortuosity, which is difficult to measure experimentally. We present pytrax: (tortuosity from random axial movements) a simple and efficient random walk method implemented in python to calculate the average tortuosity and orthogonal directional tortuosity components of an image. The code works for both two and three-dimensional images and completes a statistically significant number of walks in parallel for large images in a few minutes using a standard desktop computer. By comparison, a Lattice Boltzmann or finite element simulation on similar sized images can take several hours. Keywords: Random walk, Directional tortuosity, Python, Image analysis
ISSN:2352-7110