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

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 t...

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Bibliographic Details
Published in:Minerals (Basel) 2020-04, Vol.10 (4), p.334
Main Authors: Voigt, Marcelene, Miller, Jodie A., Mainza, Aubrey N., Bam, Lunga C., Becker, Megan
Format: Article
Language:English
Subjects:
3D data analysis
Artificial intelligence
Automation
Calibration
Computed tomography
Diameters
Earth science
Electron microscopes
Grain size
gray level co-occurrence matrices
Histograms
Image segmentation
Methods
Mineral processing
mineral texture
mineralogy
Minerals
Robustness
Statistical methods
Studies
Texture
Tomography
Tungsten
Variability
X rays
X-ray computed tomography
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Summary: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.
ISSN:2075-163X
2075-163X
DOI:10.3390/min10040334