Abstract
Grayscale skeletonization offers an interesting alternative to traditional skeletonization following a binarization. It is well known that parallel algorithms for skeletonization outperform sequential ones in terms of quality of results, yet no general and well defined framework has been proposed until now for parallel grayscale thinning. We introduce in this paper a parallel thinning algorithm for grayscale images, and prove its topological soundness based on properties of the critical kernels framework. The algorithm and its proof, given here in the 2D case, are also valid in 3D. Some applications are sketched in conclusion. © 2013 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Couprie, M., Bezerra, N., & Bertrand, G. (2013). A parallel thinning algorithm for grayscale images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7749 LNCS, pp. 71–82). Springer Verlag. https://doi.org/10.1007/978-3-642-37067-0_7
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