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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 <3,4,5> 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.

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Skeletonization will probably become as valuable a tool for shape analysis in 3D, as it is in 2D. We present a topology preserving 3D skeletonization method which computes both surface and curve skeletons whose voxels are labelled with the D distance to the original background. The surface skeleton preserves all shape information, so (close to) complete recovery of the object is possible. The curve skeleton preserves the general geometry of the object. No complex computations, large sets of masks, or extra memory are used, which make implementations e$cient. Resulting skeletons for geometric objects in a number of 2 Mbyte images are shown as examples.

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