### ESTIMATION OF TORTUOSITY AND RECONSTRUCTION OF GEODESIC PATHS IN 3D

#### Abstract

The morphological tortuosity of a geodesic path in a medium can be defined as the ratio between its geodesic length and the Euclidean distance between its two extremities. Thus, the minimum tortuosity of all the geodesic paths into a medium in 2D or in 3D can be estimated by image processing methods

using mathematical morphology. Considering a medium, the morphological tortuosities of its internal paths are estimated according to one direction, which is perpendicular to both starting and ending opposite extremities of the geodesic

paths. The used algorithm estimates the morphological tortuosities from geodesic distance maps, which are obtained from geodesic propagations. The shape of the propagated structuring element used to estimate the geodesic distance maps on a discrete grid has a direct influence on the morphological tortuosity and has to be chosen very carefully. The results of our algorithm is an image with pixels p having a value equal to the length of the shortest path containing p

and connected to two considered opposite boundaries A and B of the image. The analysis of the histogram of the morphological tortuosities gives access to their statistical distribution. Moreover, for each tortuosity the paths can be extracted from the original image, which highlights the location of them into the sample. However, these geodesic paths have to be reconstructed for further processing. The extraction, because applying a threshold on the tortuosities, results in disconnected components, especially for highly tortuous paths. This reconstruction consists in reconnecting these components to the geodesic path linking the two opposite faces, by means of a backtracking algorithm.

using mathematical morphology. Considering a medium, the morphological tortuosities of its internal paths are estimated according to one direction, which is perpendicular to both starting and ending opposite extremities of the geodesic

paths. The used algorithm estimates the morphological tortuosities from geodesic distance maps, which are obtained from geodesic propagations. The shape of the propagated structuring element used to estimate the geodesic distance maps on a discrete grid has a direct influence on the morphological tortuosity and has to be chosen very carefully. The results of our algorithm is an image with pixels p having a value equal to the length of the shortest path containing p

and connected to two considered opposite boundaries A and B of the image. The analysis of the histogram of the morphological tortuosities gives access to their statistical distribution. Moreover, for each tortuosity the paths can be extracted from the original image, which highlights the location of them into the sample. However, these geodesic paths have to be reconstructed for further processing. The extraction, because applying a threshold on the tortuosities, results in disconnected components, especially for highly tortuous paths. This reconstruction consists in reconnecting these components to the geodesic path linking the two opposite faces, by means of a backtracking algorithm.

##### Keywords

3D images; fibrous media; mathematical morphology; geodesic paths; tortuosity

DOI: 10.5566/ias.v32.p27-43