Efficient 3D curve skeleton extraction from large objects

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Abstract

Curve skeletons are used for linear representation of 3D objects in a wide variety of engineering and medical applications. The outstandingly robust and flexible curve skeleton extraction algorithm, based on generalized potential fields, suffers from seriously heavy computational burden. In this paper we propose and evaluate a hierarchical formulation of the algorithm, which reduces the space where the skeleton is searched, by excluding areas that are unlikely to contain relevant skeleton branches. The algorithm was evaluated using dozens of object volumes. Tests revealed that the computational load of the skeleton extraction can be reduced up to 100 times, while the accuracy doesn't suffer relevant damage. © 2011 Springer-Verlag.

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APA

Szilágyi, L., Szilágyi, S. M., Iclǎnzan, D., & Szabó, L. (2011). Efficient 3D curve skeleton extraction from large objects. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7042 LNCS, pp. 133–140). https://doi.org/10.1007/978-3-642-25085-9_15

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