Building Skeleton Models via 3-D Medial Surface Axis Thinning Algorithms

In this paper, we present an efficient three-dimensional (3-D) parallel thinning algorithm for extracting both the medial surfaces and the medial axes of a 3-D object (given as a 3-D binary image). A new Euler table is derived to ensure the invariance of the Euler characteristic of the object, during thinning. An octree data structure of 3 × 3 × 3 lattice points is built to examine the local connectivity. The sets of "simple" points found by different researchers are compared with the constructed set. Different definitions of "surface" points including ours are given. By preserving the topological and the geometrical conditions, our algorithm produces desirable skeletons and performs better than others in terms of noise sensitivity and speed. Pre- and postprocessors can be used to remove additional noise spurs. Its use in defect analysis of objects produced by casting and forging is discussed.