Automated optical image analysis of goethitic iron ores

Abstract

ABSTRACT To optimise processing/beneficiation procedures a detailed characterisation of goethitic ores is needed, including mineral liberation, association and textural classification. The identification of different iron oxides and oxyhydroxides is already reliably performed by optical image analysis (OIA). Automated OIA identification of different gangue materials, particularly quartz, can be problematic, however. The article demonstrates the capability of OIA software Mineral4/Recognition4 to characterise goethitic iron ores. Characterisation includes identification of the different types of goethite, hydrohematite and gangue materials such as quartz and kaolinite. XRD and XRF analysis results are compared with those from OIA. Correlation of these results and visual comparison shows that optical image analysis can be an effective tool for characterisation of low and medium grade iron ores. The work highlights issues regarding discrimination of aluminous goethite and gangue, micro and nano-porosity and effective density, for further study.