Abstract    Texture and color appearance of froth is a discreet qualitative tool for evaluating the performance of flotation process. The structure of a froth developed on the flotation cell has a significant effect on the grade and recovery of copper concentrate. In this work, image analysis and neural networks have been implemented to model and control the performance of such a system. The result reveals that these techniques can be employed to control the performance of flotation cells, improve the recovery of the copper concentrate and finally reduce the dependency of the performance on the solely observation of an operator which can be otherwise subjected to human error.

Keywords    Froths Flotation, Digital Image Processing, Copper Concentration, Neural Networks

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