Paper
6 July 1998 Three-dimensional skeletonization using distance transform
Kai Qian, Siqi Cao, Prabir Bhattacharya
Author Affiliations +
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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kai Qian, Siqi Cao, and Prabir Bhattacharya "Three-dimensional skeletonization using distance transform", Proc. SPIE 3387, Visual Information Processing VII, (6 July 1998); https://doi.org/10.1117/12.316415
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KEYWORDS
3D image processing

3D acquisition

Binary data

Image processing

Solids

Biomedical optics

Quantitative analysis

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