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This work presents vision based control of a single-axis magnetic levitation system. The  system is the fundamental of the high speed maglev trains and magnetic bearings. A ferro magnetic object is levitated at a desired position in the air gap by applying electromagnetic  force against to gravity. The system consists of five main components: a position sensor and a camera, a coil, a controller, a driver and a ferro-magnetic object. Current on the coil, which causes electromagnetic force, was controlled according to position feedback. The mathematical model of the system was obtained based on Newton’s theory and verified by experimental data. The nonlinear relationships between force, current and air gap were found experimentally. The controller was designed using feedback linearization technique based on the nonlinear relationships. In the literature, light based sensors have mostly been used to detect the object’s position. Despite the preferred usage of conventional sensors, some disadvantages are encountered such as: calibration requirement, non-linearity, noise and non robustness. These disadvantages inevitably cause disturbances on the system. In this study, the position of the magnetic object was detected using image processing methods in order to overcome the disadvantages associated with the light based sensors.