3D segment matching using the Hausdorff distance

The problem of matching sets of either points or segments is a well-studied problem with applications to image processing and computer vision and also to areas such as bioinformatics and astronomy. We present an approximate solution to the segment matching problem in 3D that can be used to recognize planar faced objects from range data. Our main contributions in the area of geometric matching are: a new definition of the Hausdorff distance between two sets of segments. This definition appears to be better suited to comparisons between sets of geometric entities. An efficient and practical strategy for approximate matching of sets of segments using this distance definition. Our solution extends results obtained for the simpler case of point-sets with the same time efficiency within the same error bounds