The retinal Image registration based on Scale Invariant Feature

Accurate retinal Image registration is essential to monitor and track the progress of various diseases. Since it is low quality images on Non-mydriatic or with the disease. Then vascular structure will become less clear. It becomes more difficult for the general registration methods. In this paper, a novel feature based retinal image registration method is proposed to solve this problem. SIFT(Scale Invariant Feature Transform) as key-point is extracted. Best-Bin-First (BBF) and keypoints´ orientations are applied to identify the corresponding features between two images. Affine model and quadric model are used to register two images, which is based on strategy of coarse to fine registration. Experimental results show that the method is robust and efficient.