The process of flotation is one of the most complex industrial processes for purifying minerals, and the control of flotation process is one of the most challenging issues in the mineral processing industry. This paper describes a method based on machine vision system to classify different grades of Antimony during the flotation process. It is proved that the size of bubbles provides valuable information about froth flotation process. The proposed machine vision system, after collecting froth flotation images of Antimony, segments each image bubbles with Extended-Maximal transform method and creates a descriptor based on bubbles perimeters. Based on different grades of Antimony, images are divided in to four classes. To classify Antimony froth images, the created descriptors are assigned to a classifier like support vector machine.

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