Abstract
This paper proposes a method for computing the medial axis transform (MAT) or the skeleton of a general 2D shape using a technique with a high performance, based on a distance transform computation from the shape’s boundaries. The distance transform is computed propagating a wavefront from the boundary, and the skeleton is obtained detecting the points where the wavefronts collide themselves, and applying connectivity rules during the process. This method has two main advantages: the efficiency and the preservation of the skeleton properties.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Blum, H.: A transformation for extracting new descriptors of shape. In: Wathen-Dunn, W. (ed.) Proc. Models for the Perception of Speech and Visual Form, pp. 362–380. MIT Press, Cambridge (1967)
Montanari, U.: A method for obtaining skeletons using a quasi-euclidean distance. Journal of the Association for Computing Machinery 15(4), 600–624 (1968)
Rosenfeld, A., Pfaltz, J.L.: Sequential operations in digital picture processing. J. Assoc. Comp. Mach. 13, 471–494 (1966)
Danielsson, P.E.: Euclidean distance mapping. Computer Graphics and Image Processing 14, 227–248 (1980)
Ammann, C.J., Sartori-Angus, A.G.: Fast thinning algorithm for binary images. Image Vision Comput. 3(2), 71–79 (1985)
Zhang, Y.Y., Wan, P.S.P.: A parallel thinning algorithm with two-subiteration that generates one-pixel-wide skeletons. In: Proceedings of International Conference on Patter Recognition, vol. 4, pp. 457–461. IEEE Computer Society, Los Alamitos (1996)
Arcelli, C., di Baja, G.S.: Finding local maxima in a pseudo-euclidean distance transformation. In: CVGIP, vol. 43, pp. 361–367 (1988)
Ogniewicz, R., Ilg, M.: Voronoi skeletons: Theory and applications. In: Proc. IEEE Conf. Computer Vision and Pattern Recognition, CVPR, pp. 63–69. IEEE Computer Society, Los Alamitos (1992)
Brandt, J.W., Algazi, V.R.: Continuous skeleton computation by Voronoi diagram. In: CVGIP Image Understanding, vol. 55, pp. 329–338 (1992)
Sugihara, K.: Approximation of generalized Voronoi diagrams by ordinary Voronoi diagrams. CVGIP: Graphical Models and Image Processing 55(6), 522–531 (1993)
Kimmel, R., Shaked, D., Kiryati, N., Bruckstein, A.M.: Skeletonization via distance maps and level sets. Computer Vision and Image Understanding: CVIU 62(3), 382–391 (1995)
Cardenes, R.: Esquemas eficientes de geometría computacional aplicados a la segmentacióon de imágenes médicas, Ph.D. thesis, University of Las Palmas de Gran Canaria (2004)
Verwer, B.H., Verbeek, P.W., Dekker, S.T.: An efficient uniform cost algorithm applied to distance transforms. IEEE Transactions on Pattern Analysis an Machine Intelligence 11(4), 425–429 (1989)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cárdenes, R., Ruiz-Alzola, J. (2005). Skeleton Extraction of 2D Objects Using Shock Wavefront Detection. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2005. EUROCAST 2005. Lecture Notes in Computer Science, vol 3643. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11556985_51
Download citation
DOI: https://doi.org/10.1007/11556985_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29002-5
Online ISBN: 978-3-540-31829-3
eBook Packages: Computer ScienceComputer Science (R0)