Abstract
Thinning is an iterative object reduction to obtain skeleton-like shape features of volumetric binary objects. Conventional thinning algorithms preserve endpoints to provide important geometric information relative to the object to be represented. An alternative strategy is also proposed that accumulates isthmuses (i.e., generalization of curve and surface interior points as skeletal elements). This paper presents two parallel isthmus-based 3D thinning algorithms that are capable of producing centerlines and medial surfaces. The strategy which is used is called subiteration-based or directional: each iteration step is composed of 12 subiterations each of which are executed in parallel. The proposed algorithms make efficient implementation possible and their topological correctness is guaranteed.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Bertrand, G., Aktouf, Z.: A 3D thinning algorithm using subfields. In: SPIE Proc. of Conf. on Vision Geometry, pp. 113–124 (1994)
Bertrand, G., Couprie, M.: Transformations topologiques discrètes. In: Coeurjolly, D., Montanvert, A., Chassery, J. (eds.) Géométrie Discrète et Images Numériques, pp. 187–209. Hermès Science Publications (2007)
Hall, R.W.: Parallel connectivity-preserving thinning algorithms. In: Kong, T.Y., Rosenfeld, A. (eds.) Topological Algorithms for Digital Image Processing, pp. 145–179. Elsevier Science B. V.(1996)
Kong, T.Y.: On topology preservation in 2–d and 3–d thinning. International Journal of Pattern Recognition and Artificial Intelligence 9, 813–844 (1995)
Kong, T.Y., Rosenfeld, A.: Digital topology: Introduction and survey. Computer Vision, Graphics, and Image Processing 48, 357–393 (1989)
Malandain, G., Bertrand, G.: Fast characterization of 3D simple points. In: Proc. 11th IEEE Internat. Conf. on Pattern Recognition, ICPR 1992, pp. 232–235 (1992)
Németh, G., Palágyi, K.: 3D parallel thinning algorithms based on isthmuses. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P., Zemčík, P. (eds.) ACIVS 2012. LNCS, vol. 7517, pp. 325–335. Springer, Heidelberg (2012)
Palágyi, K., Kuba, A.: A parallel 3D 12-subiteration thinning algorithm. Graphical Models and Image Processing 61, 199–221 (1999)
Palágyi, K., Tschirren, J., Hoffman, E.A., Sonka, M.: Quantitative analysis of pulmonary airway tree structures. Computers in Biology and Medicine 36, 974–996 (2006)
Palágyi, K.: A 3D fully parallel surface-thinning algorithm. Theoretical Computer Science 406, 119–135 (2008)
Palágyi, K., Németh, G., Kardos, P.: Topology preserving parallel 3D thinning algorithms. In: Brimkov, V.E., Barneva, R.P. (eds.) Digital Geometry Algorithms. Theoretical Foundations and Applications to Computational Imaging, pp. 165–188. Springer (2012)
Raynal, B., Couprie, M.: Isthmus-based 6-directional parallel thinning algorithms. In: Debled-Rennesson, I., Domenjoud, E., Kerautret, B., Even, P. (eds.) DGCI 2011. LNCS, vol. 6607, pp. 175–186. Springer, Heidelberg (2011)
Shaked, D., Bruckstein, A.: Pruning medial axes. Computer Vision Image Understanding 69, 156–169 (1998)
Siddiqi, K., Pizer, S. (eds.): Medial representations – Mathematics, algorithms and applications. Computational Imaging and Vision, vol. 37. Springer (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Palágyi, K. (2013). Parallel 3D 12-Subiteration Thinning Algorithms Based on Isthmuses. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2013. Lecture Notes in Computer Science, vol 8033. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41914-0_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-41914-0_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41913-3
Online ISBN: 978-3-642-41914-0
eBook Packages: Computer ScienceComputer Science (R0)