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Decomposition of Two-Dimensional Shapes by Graph-Theoretic Clustering

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2 Author(s)
Linda G. Shapiro ; ASSOCIATE MEMBER, IEEE, Department of Computer Science, Kansas State University, Manhattan, KS 66506; Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061. ; Robert M. Haralick

This paper describes a technique for transforming a twodimensional shape into a binary relation whose clusters represent the intuitively pleasing simple parts of the shape. The binary relation can be defined on the set of boundary points of the shape or on the set of line segments of a piecewise linear approximation to the boundary. The relation includes all pairs of vertices (or segments) such that the line segment joining the pair lies entirely interior to the boundary of the shape. The graph-theoretic clustering method first determines dense regions, which are local regions of high compactness, and then forms clusters by merging together those dense regions having high enough overlap. Using this procedure on handdrawn colon shapes copied from an X-ray and on handprinted characters, the parts determined by the clustering often correspond well to decompositions that a human might make.

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:PAMI-1 ,  Issue: 1 )