ML Anthology

Voronoi Skeletons: Theory and Applications

Robert L. Ogniewicz, Markus Ilg
CVPR 1992 pp. 63-69
doi:10.1109/CVPR.1992.223226 /cvpr/1992/ogniewicz1992cvpr-voronoi/

Abstract

A novel method of robust skeletonization based on the Voronoi diagram of boundary points, which is characterized by correct Euclidean metries and inherent preservation of connectivity, is presented. The regularization of the Voronoi medial axis (VMA) in the sense of H. Blum's (1967) prairie fire analogy is done by attributing to each component of the VMA a measure of prominence and stability. The resulting Voronoi skeletons appear largely invariant with respect to typical noise conditions in the image and geometric transformations. Hierarchical clustering of the skeleton branches, the so-called skeleton pyramid, leads to further simplification of the skeleton. Several applications demonstrate the suitability of the Voronoi skeleton to higher-order tasks such as object recognition.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Cite

Text

Ogniewicz and Ilg. "Voronoi Skeletons: Theory and Applications." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992. doi:10.1109/CVPR.1992.223226

Markdown

[Ogniewicz and Ilg. "Voronoi Skeletons: Theory and Applications." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992.](https://mlanthology.org/cvpr/1992/ogniewicz1992cvpr-voronoi/) doi:10.1109/CVPR.1992.223226

BibTeX

@inproceedings{ogniewicz1992cvpr-voronoi,
  title     = {{Voronoi Skeletons: Theory and Applications}},
  author    = {Ogniewicz, Robert L. and Ilg, Markus},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1992},
  pages     = {63-69},
  doi       = {10.1109/CVPR.1992.223226},
  url       = {https://mlanthology.org/cvpr/1992/ogniewicz1992cvpr-voronoi/}
}