Monitoring of Flotation Processes Using Multiresolutional Multivariate Image Analysis (MR-MIA)

This paper provides a novel machine vision solution based on multiresolutional multivariate image analysis (MR-MIA) for monitoring of flotation processes. The approach based on MR-MIA is superior to the contemporary machine vision approaches in terms of efficient analysis of morphological and color information and robustness to lighting conditions. The results show that the MR-MIA based approach provides enough morphological and color information of froth needed to describe different froth status. A PCA model built from the information provided by MR-MIA can provide multivariate control charts, from which the transition as well as steady-state process status can be monitored in real time.