PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Combining region and edge cues for image segmentation in a probabilistic Gaussian mixture framework
Omer Rotem, Hayit Greenspan and Jacob Goldberger
In: CVPR 2007, 18-23 June 2007, Minneapolis, USA.


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 for building the statistical model with color and spatial features, and we incorporate edge information based on texture, color and brightness differences into the EM algorithm. We evaluate our results qualitatively and quantitatively on a large data-set of natural images and compare our results to other state-of-the-art methods.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:3338
Deposited By:Jacob Goldberger
Deposited On:08 February 2008