A novel registration method for retinal images based on local features.

Sometimes it is very hard to automatically detect the bifurcations of vascular network in retinal images so that the general feature based registration methods will fail to register two images. In order to solve this problem, we developed a novel local feature based retinal image registration method. We first detect the corner points instead of bifurcations since corner points are sufficient and uniformly distributed in the overlaps. Second, a novel highly distinctive local feature is extracted around each corner point. These local features are invariant to rotation and contrast, and partially invariant to scaling. Third, a bilateral matching technique is applied to identify the corresponding features between two images. Finally a second order polynomial transformation is used to register two images. Experimental results show that our method is very robust and compute efficient to register retinal images even of very low quality.