The Development of a vision-based flotation froth analysis system

Master Thesis


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University of Cape Town

This dissertation describes the development of a machine vision system for the on-line analysis of flotation froth images. The size and shape of bubbles that constitute the flotation froth convey considerable information on the performance of the flotation process. A method whereby this size and shape information can be automatically extracted from froth images is highly desirable. In this research, a system was developed which acquires froth image using a video camera, and then rapidly identifies the bubbles in the froth by segmenting the image using a morphological operation known as the Fast Watershed Transform. Bubble size and shape information is extracted from the segmented images and can be correlated with metallurgical and other data from concentrator plants in order to elucidate relationships between froth appearance and plant performance. The machine vision system developed was tested on a platinum concentrator plant, and is able to identify and characterise variations in flotation froth appearance, which occur in response to changes in process inputs. The ability of the system to detect changes in bubble size distribution has been found to be particularly useful in detecting process input variations.

Bibliography : leaves157-163.