A textural approach to the geometallurgical characterisation of iron ores helps better predict ore behaviour during downstream processing. Therefore, a robust, automated, objective method for the textural characterisation of iron ores is highly relevant to the industry's needs. Utilisation of an optical image analysis (OIA) technique not only allows the reliable and consistent identification of different iron oxide and oxyhydroxide minerals, eg hematite, kenomagnetite, hydrohematite, vitreous and ochreous goethite, but also enables a distinction to be made between forms of the same mineral with differing degrees of oxidation or hydration. The CSIRO OIA system can also automatically identify particle sections with different textures and assign these sections to defined textural groups. Furthermore, recent capability developments in the CSIRO Mineral4/Recogntion4 OIA system have enabled the automatic identification of different textural forms of the same mineral, eg martite and microplaty hematite.The high resolution and imaging speed of the CSIRO OIA system have already made it possible for industry to significantly reduce the cost and subjectivity of iron ore characterisation with a simultaneous increase in the accuracy of mineral identification. Extra software modules have been recently developed to meet industry demands for enhanced productivity. The addition of a multiple block imaging module enables image acquisition for sets of polished blocks at a time, rather than separate imaging of individual blocks. The multiple set processing module allows the processing of up to 20 groups of different sets at once, where every group can contain up to 20 different sets of images that share the same analysis profile. These modules constitute a significant increase in productivity, as analyses can now be performed for many hours without the need for operator intervention, including after normal working hours, thus increasing equipment utilisation and freeing up the operator's time for other tasks.These new developments, together with the improvement of previously available features, eg identification of non-opaque minerals, automated textural classification, automated particle separation, automated correction of mineral maps and on-line measurement, means that the Mineral4/Recognition4 OIA system represents a unique, reliable, industry-focused tool for iron ore characterisation.CITATION:Donskoi, E, Poliakov, A, Manuel, J R, Peterson, M J and Hapugoda, S, 2013. Industrial strength optical image analysis system - Mineral4/Recognition4, in Proceedings Iron Ore 2013 , pp 227-242 (The Australasian Institute of Mining and Metallurgy: Melbourne).