Abstract
Binary image representation by its morphological skeleton transform has been proposed in the past as an information preserving representation. In this paper this skeleton representation is adopted as the start point for the development of a binary shape recognition scheme. A skeleton matching algorithm is presented that efficiently characterizes the similarity between two skeletons as a distance measure. This skeleton matching algorithm resembles the well known from speech processing elastic matching technique.
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