Medial Axis Approximation with Constrained Centroidal Voronoi Diagrams On Discrete Data
نویسندگان
چکیده
In this paper, we present a novel method for medial axis approximation based on Constrained Centroidal Voronoi Diagram of discrete data (image, volume). The proposed approach is based on the shape boundary subsampling by a clustering approach which generates a Voronoi Diagram well suited for Medial Axis extraction. The resulting Voronoi Diagram is further filtered so as to capture the correct topology of the medial axis. The resulting medial axis appears largely invariant with respect to typical noise conditions in the discrete data. The method is tested on various synthetic as well as real images. We also show an application of the approximate medial axis to the sizing field for triangular and tetrahedral meshing. Julien Dardenne · Sébastien Valette · Rémy Prost CREATIS-LRMN, Université de Lyon, INSA, CNRS UMR 5220, Inserm U630 E-mail: [email protected] Julien Dardenne · Nicolas Siauve AMPERE, Université de Lyon, Université Lyon 1, CNRS UMR 5005 E-mail: [email protected]
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