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Image registration using the Hausdorff fraction and virtual circles

Image registration is the process of determining the transformation which best matches, according to some similarity measure, two images of the same scene taken at different times or from different view points. We propose a new image registration method based on the similarity measure called Hausdorff fraction and a novel set of features called virtual circles. This method is guaranteed to find the best homothetic transformation, if only two virtual circles are preserved between the model and the scene. Another advantage of this method is that it is a general method that works well for most types of images. The time complexity of this method is O(n/sup 2/ +nmE/sub m/), where n and m are the number of virtual circles in scene and model respectively, and E/sub m/ is the number of edge points in the model. However, using an heuristic called circularity criterion, the number of virtual circles can be reduced allowing for faster execution times, without much loss in robustness.