Approximation of Pore Space with Ellipsoids: A Comparison of a Geometrical Method with a Statistical one

Abstract

We work with tomographic images of pore space in soil. The images have large dimensions and so in order to speed-up biological simulations (as drainage or diffusion process in soil), we want to describe the pore space with a number of geometrical primitives significantly smaller than the number of voxels in pore space. In this paper, we use the curve skeleton of a volume to segment it into some regions. We describe the method to compute the curve skeleton and to segment it with a simple segment approximation. We approximate each obtained region with an ellipsoid. The set of final ellipsoids represents the geometry of pore space and will be used in future simulations. We compare this method which we call geometrical method with the one described in the paper [8], which we name statistical method (using k-means algorithm). ? 2018 IEEE.