Computer vision systems have had great importance in research of different industrial processes. Videos and photographs have been used to characterize the bed behavior in a rotary drum; in this way, the bed motion, repose angles, trajectories, and particle velocity can be determined This work shows the development of a computer vision system that measures the bed inclination angle in industrial rotary drums. The purpose of the vision system is to capture the images when the angular velocity on the drum changes. Eventually, with the data measured during the two experiments in industrial rotary drums, we have identified two input-output models representing the slumping motion. Based on the control objective, we considered two approaches: regulation and tracking PI and PII2 controllers have been designed to show that a bed inclination angle can be stabilized for rolling motion considering plants that represent slumping motion and the inclination angle as the measured variable.