Using distance transforms to decompose 3D

Object decomposition into simpler parts greatly diminishes the complexity of a recognition task. In this paper, we present a method to decompose a 3D discrete object into nearly convex or elongated parts. Object decomposition is guided by the distance transform DT. Significant voxels in DT are identified and grouped into seeds. These are used to originate the parts of the object by applying the reverse and the constrained distance transformations. Criteria for merging less significant parts and obtaining a perceptually meaningful decomposition are also given. This approach is likely to be of interest in future applications due to the increasing number and the decreasing cost of devices for volume image acquisition.