Flotation froth image segmentation based on highlight correction and parameter adaptation

The level of automation employed in flotation production is relatively low. In an actual concentrator, operators use their judgment to adjust the production state based on the visual characteristics of the flotation froth surface. There are shortcomings, such as strong subjectivity and lagging process operation, that easily cause the waste of manpower and material resources. Machine vision technology is introduced to replace human visualization, achieving a quantitative description of the visual characteristics of the froth surface. The state variable parameters are provided for the identification of the flotation conditions.