Paper Info
Title
Extended Edge-Weighted Centroidal Voronoi Tessellation For Image Segmentation
Abstract
In this paper, we extend the basic edge-weighted centroidal Voronoi tessellation model (EWCVT) for image segmentation to a new advanced model, namely fuzzy and harmonic EWCVT model. This extended model introduces a fuzzy and harmonic form of clustering energy by combining the image intensity with cluster boundary information. Compared with the classic CVT and EWCVT methods, the fuzzy and harmonic EWCVT algorithm can not only overcome the sensitivity to the initialization and noise, but also improve the accuracy of clustering results, as verified in several biomedical images.
Year
DOI
Venue
2014
10.1007/978-3-319-09994-1_15
Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications
Keywords
Field
DocType
centroidal Voronoi tessellation, fuzzy and harmonic model, image segmentation
Computer vision,Centroidal Voronoi tessellation,Fuzzy logic,Harmonic,Algorithm,Image segmentation,Lloyd's algorithm,Artificial intelligence,Initialization,Cluster analysis,Mathematics
Conference
Volume
ISSN
Citations 
8641
0302-9743
0
PageRank 
References 
Authors
0.34
16
2
Name
Order
Citations
PageRank
Kangkang Hu142.42
Yongjie Zhang229334.45