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.
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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)
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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
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DOI: https://doi.org/10.1007/11556985_51
Publisher Name: Springer, Berlin, Heidelberg
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