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 compound multinomial (DCM) probability density to model the mixing proportions (i.e., the probabilities of class labels) and a Gauss

• Type: Journal
• Year: 2010
• Where: TIP
• Authors: Christophoros Nikou, Aristidis Likas, Nikolas P. Galatsanos
• Keywords: Education, Image Segmentation, Mixing Proportions, Model, TIP 2010