Abstract
Skeleton is a shape descriptor which summarizes the general form of objects. It can be expressed in terms of the fundamental morphological operations. The limitation of that characterization is that its construction based on digital disks such that cannot provide good approximation to the Euclidean disks. In this paper we define a new type of skeleton based on neighborhood sequences that is much closer to the Euclidean skeleton. A novel method for quantitative comparison of skeletonization algorithms is also proposed.
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Fazekas, A., Palágyi, K., Kovács, G., Németh, G. (2008). Skeletonization Based on Metrical Neighborhood Sequences. In: Gasteratos, A., Vincze, M., Tsotsos, J.K. (eds) Computer Vision Systems. ICVS 2008. Lecture Notes in Computer Science, vol 5008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79547-6_32
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DOI: https://doi.org/10.1007/978-3-540-79547-6_32
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