A fuzzy edge-weighted centroidal Voronoi tessellation model for image segmentation

DOI10.1016/j.camwa.2015.11.003zbMath1443.94013OpenAlexW2186947347MaRDI QIDQ2007268

Xiaochuan Fan, Xiaoqiang Wang, Lili Ju, Wang, Song

Publication date: 12 October 2020

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2015.11.003

zbMATH Keywords

fuzzy clusteringimage segmentationedge-weighted centroidal Voronoi tessellation

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Computer graphics; computational geometry (digital and algorithmic aspects) (68U05) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Uses Software

• AS 58
• AS 136

Cites Work

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• Algorithm AS 136: A K-Means Clustering Algorithm
• Fast and robust fuzzy \(c\)-means clustering algorithms incorporating local information for image segmentation
• Probabilistic methods for centroidal Voronoi tessellations and their parallel implementations
• Centroidal Voronoi tessellation algorithms for image compression, segmentation, and multichannel restoration
• Printer graphics for clustering
• Active contours without edges
• Constrained Centroidal Voronoi Tessellations for Surfaces
• Centroidal Voronoi Tessellations: Applications and Algorithms
• An Edge-Weighted Centroidal Voronoi Tessellation Model for Image Segmentation
• A Robust Fuzzy Local Information C-Means Clustering Algorithm
• Image Segmentation Using Local Variation and Edge-Weighted Centroidal Voronoi Tessellations

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