One approach to pattern recognition is to use a template from a database
of objects and match it to a probe image containing the unknown.
Accordingly, the Hausdorff distance can be used to measure the similarity
of two sets of points. In particular, the Hausdorff can measure the
goodness of a match in the presence of occlusion, clutter, and noise.
However, existing 3D algorithms for calculating the Hausdorff are
computationally intensive, making them impractical for pattern
recognition that requires scanning of large databases. The present
invention is directed to a new method that can efficiently, in time and
memory, compute the Hausdorff for 3D range imagery. The method uses a
window-based approach.