Iterative neural networks for skeletonization and thinning

Skeletons provide a compact and elegant description of the shape of binary objects. They are usually obtained by performing a distance transformation on the original binary data or by thinning. In this paper we summarize some of the existing techniques in this area and introduce iterative neural networks for skeletonization and thinning. The networks are trained to learn a deletion rule and they iteratively delete points from the objects until only the skeleton remains. 1.