A Machine Vision Based Method for Extracting Visual Features of Froth in Copper Floatation Process

Abstract

Froth flotation is one of the most important and widespread methods of separation of minerals and waste materials and at the same time one of the most accurate methods of refining low-grade metal minerals. This paper presents a method for visual feature extraction of froth bubbles including the size, color, shape, and mobility based on machine vision and image processing techniques. The proposed method is capable of identifying bubbles properties as well as estimating their velocity and direction of movement. The performance of the proposed method is evaluated using real videos captured from the copper floatation process. The method description, as well as simulation results, are presented.