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