Abstract
In this paper, we propose a novel set of image features called virtual circles, and their use in an efficient image registration algorithm to find translation and scale differences. A virtual circle is a circle with maximal radius encompassing a background area that does not contain edge points. Virtual circles have a number of nice properties such as the fact that they can be extracted efficiently with the help of the distance transform from many types of images. They can also have extra information, such as their radii, which can be used for efficient registration. Furthermore, virtual circles are robust against broken or corrupt edges. On the other hand, they are vulnerable to background noise, but through the use of a heuristic called the smoothness criterion, virtual circles that are less likely to be corrupted by background noise can be selected. Another advantage of the smoothness criterion is that it reduces the number of virtual circles needed, which increases the efficiency of the algorithm.