A computationally efficient algorithm for shape decomposition

An algorithm is described that is capable of decomposing homogeneous image regions into a complete set of convex parts ordered by size. The process is information-preserving and computationally efficient, and does not require prior edge smoothing. Shape decomposition is useful for parsing undersegmented image regions into which parts correspond to separate semantic entities. The algorithm is efficient because it operates on a list-oriented form of shape representation. Results of decomposing several different shapes are presented and discussed