This paper presents a new approach to segmentation-driven retinal image registration. The proposed algorithm aims to help physicians to detect changes that occur in the blood vasculature due to various diseases. The proposed approach uses multiscale products, which augment the difference between blood vessels and the rest of the retina. The result of scale multiplication is then iteratively thresholded in order to obtain a binary map of vessels inside the retina. For the registration part, the centre of the optic disc is detected and used as control point. Having determined both the position of the blood vessels and the centre of the optic disc, translational and rotational differences between the images can be eliminated and registration can be achieved. The centroid of the optic disc is used as the center of rotation. The final registration is then achieved by searching the best match between the two images using a XOR operation.