The classification of industrial sand-ores by image recognition methods

The chemical and physical composition of the feldspar-quartz sand-ore differ from location to location in a given open pit mine and the utilisation of the raw-ore, as well as its resale value will depend on these properties. Thus, a very important aspect of the operation is to determine quickly and accurately the properties of the sand at a given location. The aim of this paper is to formulate a pattern recognition algorithm and use it to classify, with a very low probability of error, samples of sand-ore of given classes. Such classification should be fast and online, so that the sand grabber can use the information automatically. The algorithm presented operates in two stages. In the first stage of operation, classification has been accurate over 92%, while after the refinement stage, precision has reached on average 96%. Details are given on how to implement this algorithm online in an actual production process