Abstract
Eccentricity measures the shortest length of the paths from a given vertex v to reach any other vertex w of a connected graph. Computed for every vertex v it transforms the connectivity structure of the graph into a set of values. For a connected region of a digital image it is defined through its neighbourhood graph and the given metric. This transform assigns to each element of a region a value that depends on it's location inside the region and the region's shape. The definition and several properties are given. Presented experimental results verify its robustness against noise, and its increased stability compared to the distance transform. Future work will include using it for shape decom-position, representation, and matching. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Kropatsch, W. G., Ion, A., Haxhimusa, Y., & Flanitzer, T. (2006). The eccentricity transform (of a digital shape). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4245 LNCS, pp. 437–448). Springer Verlag. https://doi.org/10.1007/11907350_37
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