Abstract
The Rotational Haar Wavelet Transform (RHWT) method, that mimics human cognition to automate soil fabric characterization, is presented. An image of a soil is divided into numerous subareas, for which pattern directions are obtained, and then used to develop a fabric rose diagram and parameters for a cross-anisotropic fabric tensor. Based on the images of eleven sand and three rice specimens at loose and dense conditions, a strong functional relationship is shown for the fabric vector magnitude based on particle sphericity and relative density. Furthermore, a very simple and practical relationship is presented for the fabric vector magnitude based only on the relative density and the void ratio at 50% relative density.
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