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• W2133141088 startingPage "1844" @default.
• W2133141088 abstract "Centroidal Voronoi tessellations (CVTs) are special Voronoi tessellations whose generators are also the centers of mass (centroids) of the Voronoi regions with respect to a given density function and CVT-based methodologies have been proven to be very useful in many diverse applications in science and engineering. In the context of image processing and its simplest form, CVT-based algorithms reduce to the well-known <i xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>k</i> -means clustering and are easy to implement. In this paper, we develop an edge-weighted centroidal Voronoi tessellation (EWCVT) model for image segmentation and propose some efficient algorithms for its construction. Our EWCVT model can overcome some deficiencies possessed by the basic CVT model; in particular, the new model appropriately combines the image intensity information together with the length of cluster boundaries, and can handle very sophisticated situations. We demonstrate through extensive examples the efficiency, effectiveness, robustness, and flexibility of the proposed method." @default.
• W2133141088 created "2016-06-24" @default.
• W2133141088 creator A5013702415 @default.
• W2133141088 creator A5075877965 @default.
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• W2133141088 date "2009-08-01" @default.
• W2133141088 modified "2023-09-29" @default.
• W2133141088 title "An Edge-Weighted Centroidal Voronoi Tessellation Model for Image Segmentation" @default.
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• W2133141088 doi "https://doi.org/10.1109/tip.2009.2021087" @default.
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• W2133141088 hasPublicationYear "2009" @default.
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