Minimum Description Length Based 2 D Shape DescriptionMengxiang

In this paper, we present an approach for 2{D shape description based on the Minimum-Description-Length (MDL) criterion. Using this criterion, we can derive, for a given data set and a class of models, a description which best explains the data. The problems of contour partitioning, colinear and cocurvilinear segment grouping, and classiication of 2{D contours in terms of straight and curved, are formulated in a particular description language and the MDL criterion is applied, the shortest description is accepted as the \explanation" of the data. The algorithm has been implemented and tested on a variety of real images, giving reasonable results. The work presented in the paper was performed under the ESPRIT-BRA 3038 Vision as Process (VAP) project. The support from the Swedish National Board for Industrial and Technical Development, NUTEK, is gratefully acknowledged. Discussion with and comments from Jan-Olof Eklundh, GG oran Olofsson, and Lars Olsson are very much appreciated.