Using geometric properties for correspondence-less image alignment

We describe a framework for image alignment that does not use explicit feature correspondences. We show how certain geometric properties of image contours are related to the parameters of the geometric transformation between the images. For a transformation model, we show how to recover the transformation parameters using simple statistical distributions of geometric properties. The use of these statistical descriptions eliminates the need for establishing explicit feature correspondence. The proposed method is robust to problems of occlusion, clutter and errors in low-level processing. We demonstrate the effectiveness of our method on real images.