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CVPR
2008
IEEE
15 years 23 days ago
Edge preserving spatially varying mixtures for image segmentation
A new hierarchical Bayesian model is proposed for image segmentation based on Gaussian mixture models (GMM) with a prior enforcing spatial smoothness. According to this prior, the...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. Ga...
MICCAI
2008
Springer
14 years 12 months ago
MR Brain Tissue Classification Using an Edge-Preserving Spatially Variant Bayesian Mixture Model
In this paper, a spatially constrained mixture model for the segmentation of MR brain images is presented. The novelty of this work is a new, edge preserving, smoothness prior whic...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. ...
TIP
2010
167views more  TIP 2010»
13 years 5 months ago
A Bayesian Framework for Image Segmentation With Spatially Varying Mixtures
Abstract--A new Bayesian model is proposed for image segmentation based upon Gaussian mixture models (GMM) with spatial smoothness constraints. This model exploits the Dirichlet co...
Christophoros Nikou, Aristidis Likas, Nikolas P. G...
JMIV
2010
87views more  JMIV 2010»
13 years 9 months ago
Spatially Varying Mixtures Incorporating Line Processes for Image Segmentation
Giorgos Sfikas, Christophoros Nikou, Nikolas P. Ga...
CVPR
2007
IEEE
15 years 23 days ago
Combining Region and Edge Cues for Image Segmentation in a Probabilistic Gaussian Mixture Framework
In this paper we propose a new segmentation algorithm which combines patch-based information with edge cues under a probabilistic framework. We use a mixture of multiple Gaussians...
Omer Rotem, Hayit Greenspan, Jacob Goldberger