Volume decomposition and hierarchical skeletonization

Skeletons and shape components are important shape features, and they are useful for shape description and shape understanding. Techniques to extract these features from volume data are analyzed in this paper based on multiple distance transformations. This work includes an establishment of the hierarchical structure of the object volume, a decomposition of the volume into simple sub-volumes, an extraction of compact skeleton segments corresponding to each independent sub-volume, and a connection of these skeleton segments into a hierarchical structure corresponding to that of the original volume. Applications of this algorithm can be shape recognition, shape measurement, navigation planning, and others.