Title :
An efficiently computable metric for comparing polygonal shapes
Author :
Arkin, Esther M. ; Chew, L. Paul ; Huttenlocher, Daniel P. ; Kedem, Klara ; Mitchell, Joseph S B
Author_Institution :
Cornell Univ., Ithaca, NY, USA
fDate :
3/1/1991 12:00:00 AM
Abstract :
A method for comparing polygons that is a metric, invariant under translation, rotation, and change of scale, reasonably easy to compute, and intuitive is presented. The method is based on the L2 distance between the turning functions of the two polygons. It works for both convex and nonconvex polygons and runs in time O(mn log mn), where m is the number of vertices in one polygon and n is the number of vertices in the other. Some examples showing that the method produces answers that are intuitively reasonable are presented
Keywords :
computational geometry; computer vision; L2 distance; computational geometry; computer vision; convex; nonconvex; polygonal shapes; turning functions; Computer science; Computer vision; Cost function; Geometry; Image recognition; Machine vision; Rotation measurement; Shape measurement; Solid modeling; Turning;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
