Approximation of Pore Space with Ellipsoids: A Comparison of a Geometrical Method with a Statistical one
| Autor: | Lucie Druoton, Sebti Foufou, Abdelaziz Bouras, Olivier Monga, Dominique Michelucci |
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| Rok vydání: | 2018 |
| Předmět: |
Ellipsoids
Geometry 02 engineering and technology Image segmentation 010502 geochemistry & geophysics computer.software_genre Curve skeleton 01 natural sciences Ellipsoid Physics::Geophysics Set (abstract data type) Segmentation Diffusion process Voxel Simple (abstract algebra) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Cluster analysis Pore space approximation computer 0105 earth and related environmental sciences Mathematics |
| Zdroj: | SITIS |
| Popis: | 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. This publication was made possible by NPRP grant #9-390-1-088 from the Qatar National Research Fund. The findings achieved herein are solely the responsibility of the authors. Scopus |
| Databáze: | OpenAIRE |
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