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Proceedings Paper

Three-dimensional skeletonization using distance transform
Author(s): Kai Qian; Siqi Cao; Prabir Bhattacharya
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Paper Abstract

Skeletonization as a tool for quantitative analysis of three- dimensional (3D) images is becoming more important, as they are more common in a number of application fields, especially in biomedical tomographic images at different scales. Here we propose a method, which computes both surface and curve skeletons of 3D binary images. The distance transform algorithm is applied to reduce a 3D object to a 2D surface skeleton, an then to a 1D curve skeleton in two phases. In surface skeletonization, 6-connectivity is used in distance transform; while in curve skeletonization, 18-connectivity is used in computing distance transform. Some examples are discussed to illustrate the algorithm.

Paper Details

Date Published: 6 July 1998
PDF: 5 pages
Proc. SPIE 3387, Visual Information Processing VII, (6 July 1998); doi: 10.1117/12.316415
Show Author Affiliations
Kai Qian, Southern Polytechnic State Univ. (United States)
Siqi Cao, Univ. of Nebraska/Lincoln (United States)
Prabir Bhattacharya, Univ. of Nebraska/Lincoln (United States)


Published in SPIE Proceedings Vol. 3387:
Visual Information Processing VII
Stephen K. Park; Richard D. Juday, Editor(s)

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