Ka-me: A voronoi image analyzer

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Abstract

Summary: Ka-me is a Voronoi image analyzer that allows users to analyze any image with a convex polygonal tessellation or any spatial point distribution by fitting Voronoi polygons and their dual, Delaunay triangulations, to the pattern. The analytical tools include a variety of graph theoretic and geometric tools that summarize the distribution of the numbers of edges per face, areas, perimeters, angles of Delaunay triangle edges (anglograms), Gabriel graphs, nearest neighbor graphs, minimal spanning trees, Ulam trees, Pitteway tests, circumcircles and convexhulls, as well as spatial statistics (Clark-Evans Nearest Neighborhood and Variance to Mean Ratio) and export functions for standard relationships (Lewis's Law, Desch's Law and Aboav-Weaire Law). © The Author(s) 2012. Published by Oxford University Press.

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Khiripet, N., Khantuwan, W., & Jungck, J. R. (2012). Ka-me: A voronoi image analyzer. Bioinformatics, 28(13), 1802–1804. https://doi.org/10.1093/bioinformatics/bts253

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