Comparison of Seven Texture Analysis Indices for Their Applicability to Stereological Correction of Mineral Liberation Assessment in Binary Particle Systems

Abstract

An effective correction method for stereological bias is required because of the importance of accurate assessment of mineral liberation of ore particles. Stereological bias is error caused by the estimation of a three-dimensional liberation state based on two-dimensional sectional measurements. Recent studies have proposed a stereological correction method based on sectional particle texture analysis, which employs numerical particle models. However, the applicability of this method to unfamiliar particle systems, with different shape and texture characteristics from the numerical particle model, has not been thoroughly investigated. In this study, the viability of the method for examination of the internal structure and shape of unfamiliar particles, was assessed using four types of particle systems, based on combinations of two types of internal structures (Boolean and Voronoi) and two types of particle shapes (spherical and irregular). Seven different texture analysis indices were utilized for composition distribution correction with regard to each of the four types of particle systems. The results suggested that a model based on the angular second moment and/or entropy, employed by the spatial gray level dependence method, showed the greatest viability for assessment of unfamiliar particle internal structure and/or shape.

Keywords

• fractal dimension
• gray level difference method (GLDM)
• mineral liberation
• spatial gray level dependence method (SGLDM)
• stereological bias
• texture analysis