Estimation of Hydraulic Conductivity from Boring Core Images Using Texture and Color Information

Abstract

We propose a method for estimating hydraulic conductivity using texture and color information from boring core images. As texture information, 14 features are computed from a density co-occurrence matrix that is invariant with respect to image translation, scaling, and rotation in π/4 radian incremants. Hue, saturation, and value are used as color information. Multiple regression analysis is performed hydraulic conductivity as the objective variable and texture and color information as explanatory variables. To verify the effectiveness of the proposed method, we conducted an experiment using boring core collected at the site of Mie Elementary Schoool in Shimabara City, Nagasaki Prefecture, Japan.