Skeletonization of gray-scale images by gray weighted distance transform

Kai Qian; Siqi Cao; Prabir Bhattacharya

doi:10.1117/12.280625

22 July 1997 Skeletonization of gray-scale images by gray weighted distance transform

Kai Qian, Siqi Cao, Prabir Bhattacharya

Proceedings Volume 3074, Visual Information Processing VI; (1997) https://doi.org/10.1117/12.280625
Event: AeroSense '97, 1997, Orlando, FL, United States

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.

Citation Download Citation

Kai Qian, Siqi Cao, and Prabir Bhattacharya "Skeletonization of gray-scale images by gray weighted distance transform", Proc. SPIE 3074, Visual Information Processing VI, (22 July 1997); https://doi.org/10.1117/12.280625

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