Computing the maximum clique in the visibility graph of a simple polygon
Journal of Discrete Algorithms
Rectification of the chordal axis transform skeleton and criteria for shape decomposition
Image and Vision Computing
3D shape recursive decomposition by Poisson equation
Pattern Recognition Letters
A method for detecting correspondences in a sequence of modifying shapes
Pattern Recognition Letters
On a conceptual description of images
Pattern Recognition Letters
Unsolved problems in visibility graphs of points, segments, and polygons
ACM Computing Surveys (CSUR)
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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.