Determination of mineral phase percentages in ore samples by image analysis: an example from the Neves-Corvo Mine (Portugal)

Quantitative mineral characterisation is one of the fundamental subjects in mineral processing studies, providing information about the mineral species constituting an ore and on their arrangement (texture). Furthermore the same procedures applied to products resulting from one or more stages of processing (comminution, classification, separation) can give useful information about the mineral species arrangement inside the particle, permitting this way the definition of suitable separation function. Recent developments in image analysis techniques enable today to automatically analyse digital images at a low cost and in a fast way. A research exploring the possibility of getting automated mineral classification at microscopic scale based on image analysis, is presented. The study was applied to ore samples coming from the giant Neves-Corvo volcanogenic massive sulphide (VMS) deposit, located in the Iberian Pyrite Belt, southern Portugal. The studied ores are composed of very fine mineral intergrowth, getting the mineral separation very difficult. Aim of the study was to set up a procedure to determine the mineral phase percentages directly on polished sections starting from multispectral (RGB) digital images acquired under the reflected light optical microscope. The applied techniques are based on multispectral classification procedures, extensively used in remote sensing.