The Robustness of the Gray Level Co-Occurrence Matrices and X-Ray Computed Tomography Method for the Quantification of 3D Mineral Texture

• Main Authors: Marcelene Voigt, Jodie A. Miller, Aubrey N. Mainza, Lunga C. Bam, Megan Becker
• Format: Article
• Language: English
• Published: MDPI AG 2020-04-01
• Series: Minerals
• Subjects: X-ray computed tomography; gray level co-occurrence matrices; mineral texture; 3D data analysis; mineralogy
• Online Access: https://www.mdpi.com/2075-163X/10/4/334

Mineral textural quantification methods have become critical in both geosciences and mineral processing as mineral texture is a critical factor contributing to ore variability. However, the lack of objective mineral texture classification has made quantification difficult. The aim of this study is therefore to investigate the robustness of applying the gray level co-occurrence matrices (GLCM) to 3-dimensional (3D) gray scale images measured by X-ray computed tomography (XCT) for the quantification of mineral texture in 3D. The data quality of the GLCM outputs like statistics, heat maps and histograms in response to changes in XCT conditions such as artefacts, resolution, and calibration was tested. The response of the GLCM outputs with respect to different mineral texture types with anisotropic features and inter-sample variability was also explored. The methodology included testing core sizes of 26, 19, 14, and 6 mm diameter. Calibration was tested using copper and tungsten wires. The study demonstrated the versatility of the method for different sample types. Inter-sample calibration and optimal scanning conditions (quality and integrity) were also demonstrated, and a basic link between the 3D GLCM statistical descriptors with the mineral texture features of rocks was established. The 3D mineral texture method can potentially bypass the XCT segmentation process for direct automation of 3D mineral texture information.