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Proceedings Paper

Minimized morphological skeleton based on structuring-element shape analysis
Author(s): Tun-Wen Pai; John H. L. Hansen
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Paper Abstract

The digital morphological skeleton representation provides a means of improving lossless coding in a communication system. This is due to the observation that the entropy of a morphological skeleton is less than its original image. One way to improve coding efficiency is to minimize the morphological skeleton representation by choosing a more appropriate structuring element. For an image with consistent shape distribution such as a texture pattern, a more efficient and useful skeleton representation is expected. Analysis of simulated and natural image patterns show the activated points in a morphological skeleton to range between 30 and 327 points using different structuring elements. A procedure is proposed which allows for the selection of a more effective structuring element from a basis set of structuring elements. The decision process is based on the minimum-distance measurement in a multiprototype pattern classification. The structuring element for morphological skeletonization is from the closest match between the chain code edge vector and the basis set of structuring elements. The proposed procedure represents an organized means for choosing a more meaningful structuring element for morphological analysis. It is shown that a significant reduction in the number of required activated skeleton points will result for morphological skeletonization.

Paper Details

Date Published: 16 December 1992
PDF: 12 pages
Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); doi: 10.1117/12.130871
Show Author Affiliations
Tun-Wen Pai, Duke Univ. (Taiwan)
John H. L. Hansen, Duke Univ. (United States)

Published in SPIE Proceedings Vol. 1766:
Neural and Stochastic Methods in Image and Signal Processing
Su-Shing Chen, Editor(s)

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