A Geometrical Approach to Polygonal Dissimilarity and Shape Matching

Two geometrical measures have been proposed to quantify the dissimilarity between two irregular polygons. These measures capture the intuitive notion of the dissimilarity between shapes and are related to the minimum value of the intersecting area of the polygons on superposing one on the other in various configurations. A more easily computable measure of dissimilarity, referred to as the minimum integral square error between the polygons, has also been proposed, and using the latter measure pattern classification, has been performed. Experimental results involving the classification of the noisy boundaries of the four Great Lakes, Erie, Huron, Michigan, and Superior, using this measure, have been presented.