Paper
4 January 1995 Skeletonization via distance maps and level sets
Ron Kimmel, Doron Shaked, Nahum Kiryati, Alfred M. Bruckstein
Author Affiliations +
Proceedings Volume 2356, Vision Geometry III; (1995) https://doi.org/10.1117/12.198602
Event: Photonics for Industrial Applications, 1994, Boston, MA, United States
Abstract
The medial axis transform (MAT) of a shape, better known as its skeleton, is frequently used in shape analysis and related areas. In this paper a new approach for determining the skeleton of an object, is presented. The boundary is segmented at points of maximal positive curvature and a distance map from each of the segments is calculated. The skeleton is then located by applying simple rules to the zero sets of distance maps differences. A framework is proposed for numerical approximation of distance maps that is consistent with the continuous case, hence does not suffer from digitization bias due to metrication errors of the implementation on the grid. Subpixel accuracy in distance map calculation is obtained by using gray level information along the boundary of the shape in the numerical scheme. The accuracy of the resulting efficient skeletonization algorithm is demonstrated by several examples.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ron Kimmel, Doron Shaked, Nahum Kiryati, and Alfred M. Bruckstein "Skeletonization via distance maps and level sets", Proc. SPIE 2356, Vision Geometry III, (4 January 1995); https://doi.org/10.1117/12.198602
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Cited by 4 scholarly publications.
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KEYWORDS
Image segmentation

Vision geometry

Shape analysis

Wave propagation

Binary data

Wavefronts

Distance measurement

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