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This paper presents a fast algorithm for object tracking in an image sequence. It is a method that models the borders of the image as onedimensional histograms which are then used instead of templates in the matching procedure. The algorithm models the item being tracked as well as the background in the vicinity so as to then suppress it. It uses cross correlation to find the best match and weighted average to renew the model.