摘要
OIA （optical image analysis） has traditionally been used for reliable identification of different iron oxides and oxyhydroxides in iron ore. The automated CSIRO OIA system Mineral 4/Recognition 4 was created for rapid mineral and textural charaeterisation of iron ore providing identification of different minerals and different morphologies. The technique has further been applied to processed iron ore products such as iron ore sinter to determine key parameters such as porosity, different morphologies of hematite （primary and secondary）, and different morphologies of SFCA （silicon ferrite of calcium and alumininm）. Application of textural identification has recently been extended to coke characterisation where the software gives comprehensive characterisation of porosity, IMDC （inert material derived components）, RMDC （reactive material derived components） and the boundaries between IMDC and RMDC. The software also has many unique features needed for iron ore research including characterisation of large objects like pellets and ore lumps; automated gangue （including quartz） identification; automated particle separation; multiple image set processing and on-line measurements. All these features make the Mineral 4/Recognition 4OIA system a unique, reliable, industry/research focused tool for ore, sinter, pellet and coke characterisation.
