Affine invariant comparison of point-sets using convex hulls and hausdorff distances
Many object recognition or identification applications involve comparing features associated with point-sets. This paper presents an affine invariant point-set matching technique which measures the similarity between two point-sets by embedding them into an affine invariant feature space. The developed technique assumes no a priori knowledge of reference points, as is the case in many identification problems. Reference points of a point-set are obtained based on its convex hull. An enhanced version of the Modified Hausdorff Distance is also introduced and used in the feature space for comparing two point-sets. It should be noted that the technique does not attempt to obtain correspondences between the point-sets. The introduced technique is applied to two real databases and its performance is found favorable as compared to three other affine invariant matching techniques.
affine invariant convex hull hausdorff distance point-pattern comparison shape matching