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This paper investigates the feasibility and accuracy of tracking the motion of a lung tumour in a breathing phantom using a computer vision algorithm and electronic portal images. A multi-resolution optical flow algorithm that incorporates weighting based on the differences between frames is used to obtain a set of vectors corresponding to the motion between two frames. A global value representing the average motion is obtained by computing the average weighted mean from the set of vectors. The tracking accuracy of the optical flow algorithm is compared to potentiometer measurements. A self-resetting technique has been used to offset the drift observed in the cumulative position of the target. For a 12 breaths/min motion, a maximum average inter-frame velocity error of (1.06 ± 0.61) mm/s is obtained. A correlation coefficient of 0.97 bounded by a 95% prediction interval of (0.96, 0.98) is established between the optical flow and potentiometer results. Maximum absolute average positional error of 0.42 ± 0.21 mm is achieved. This approach offers the potential of real-time tumour motion tracking.