Measuring Statistical Geometric Properties of Tomographic Images of Soils

Porous media modeling is relevant in several applications, such as agricultural engineering, where soil compaction analysis requires the estimation of soil transport properties. For example, the prediction of root growing patterns and their environmental impact is usually measured by analyzing soil fluid infiltration capacity and water retention. Recently, tomographic images have been used in nondestructive tests of soil. However, using such images is challenging for two reasons: (1) Tomographic images are usually noisy, which complicates their segmentation, and (2) modeling the soil structure requires establishing adjacency relations among neighboring tomographic slices, which has a significant computational cost due to the combinatorial nature of this problem. In this paper, we propose a solution for both problems. The experimental results show that soil samples can be analyzed and classified with significant accuracy using our proposed approach.