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Proceedings Paper

Skeletonization of gray-scale images by gray weighted distance transform
Author(s): Kai Qian; Siqi Cao; Prabir Bhattacharya
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Paper Abstract

In pattern recognition, thinning algorithms are often a useful tool to represent a digital pattern by means of a skeletonized image, consisting of a set of one-pixel-width lines that highlight the significant features interest in applying thinning directly to gray-scale images, motivated by the desire of processing images characterized by meaningful information distributed over different levels of gray intensity. In this paper, a new algorithm is presented which can skeletonize both black-white and gray pictures. This algorithm is based on the gray distance transformation and can be used to process any non-well uniformly distributed gray-scale picture and can preserve the topology of original picture. This process includes a preliminary phase of investigation in the 'hollows' in the gray-scale image; these hollows are considered not as topological constrains for the skeleton structure depending on their statistically significant depth. This algorithm can also be executed on a parallel machine as all the operations are executed in local. Some examples are discussed to illustrate the algorithm.

Paper Details

Date Published: 22 July 1997
PDF: 5 pages
Proc. SPIE 3074, Visual Information Processing VI, (22 July 1997); doi: 10.1117/12.280625
Show Author Affiliations
Kai Qian, Georgia Southwestern 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. 3074:
Visual Information Processing VI
Stephen K. Park; Richard D. Juday, Editor(s)

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