Distance-Driven Skeletonization in Voxel Images

Authors:
Carlo Arcelli;Gabriella Sanniti di Baja;Luca Serino
Affiliations:
Institute of Cybernetics "E.Caianiello," CNR, Naples;Institute of Cybernetics "E.Caianiello," CNR, Naples;Institute of Cybernetics "E.Caianiello," CNR, Naples
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
2011

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Abstract

A distance-driven method to compute the surface and curve skeletons of 3D objects in voxel images is described. The method is based on the use of the weighted distance transform, on the detection of anchor points, and on the application of topology preserving removal operations. The obtained surface and curve skeletons are centered within the object, have the same topology as the object, and have unit thickness. The object can be almost completely recovered from the surface skeleton since this includes almost all of the centers of maximal balls of the object. Hence, the surface skeleton is a faithful representation. In turn, though only partial recovery is possible from the curve skeleton, this still provides an appealing representation of the object.