Characterisation of flotation froth colour and structure by machine vision

It is well known and well recognised that flotation is a process that is co mplex to monitor and study if a classical approach based on the evaluation of the signals resulting from sensors is adopted. Sensors are usually strat egically positioned in the bank cells and detect global process variables s uch as pH, reagent addition, froth level, on-stream chemical analysis, part icle size distribution, etc. In the last ten years several studies have bee n carried out with the main goal to utilise imaging techniques to detect fr oth bubbles characteristics and to evaluate the flotation process performan ce. In this paper an approach of this type is described. More specifically, image processing techniques to automatically measure the colour and the st ructure of the froth bubbles are presented and the results are discussed. A ll the investigations are carried out on digital sample images collected in an industrial flotation plant operating in steady-state conditions. The co lour analysis is performed on the whole surface of the froth images conside ring different colour reference systems (RGB, HSV, HSI); the morphological measurements are obtained after the application of selected enhancement and segmentation techniques, necessary to consider the bubbles as separate dom ains. The multiple correlation analysis performed between froth mineral con centrations (Cu, MgO, Zn and Pb content) and the extracted colour and struc ture parameters are good in most situations. (C) 2001 Elsevier Science Ltd. All rights reserved.