IEEE Trans Image Process - Image segmentation using local variation and edge-weighted centroidal Voronoi tessellations.

Tópicos

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Resumo

The classic centroidal Voronoi tessellation (CVT) model and its generalizations work quite well at extracting uniformly colored objects, but often fail to handle images with distinct color distribution or strong inhomogeneous intensity. To resolve this problem within the CVT methodology, in this paper we incorporate the information of local variation of colors/intensities and the length of boundaries into the energy functional and develop a new model called the Local Variation and Edge-Weighted Centroidal Voronoi Tessellation (LVEWCVT) for image segmentation. Its mathematical formulation and practical implementations are also discussed and given. We test the LVEWCVT method on various type of segments and also compare it with several state-of-art algorithms using extensive segmentation examples, the results demonstrate excellent performance and competence of the proposed method.

Resumo Limpo

classic centroid voronoi tessel cvt model general work quit well extract uniform color object often fail handl imag distinct color distribut strong inhomogen intens resolv problem within cvt methodolog paper incorpor inform local variat colorsintens length boundari energi function develop new model call local variat edgeweight centroid voronoi tessel lvewcvt imag segment mathemat formul practic implement also discuss given test lvewcvt method various type segment also compar sever stateofart algorithm use extens segment exampl result demonstr excel perform compet propos method

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