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Soft Image Segmentation Based on the Mixture of Gaussians and the Phase-Transition Theory

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DOI: 10.4236/am.2014.518275    2,427 Downloads   2,952 Views   Citations

ABSTRACT

In this paper, we propose a new soft multi-phase segmentation model where it is assumed that the pixel intensities are distributed as a Gaussian mixture. The model is formulated as a minimization problem through the use of the maximum likelihood estimator and phase-transition theory. The mixture coefficients, which are estimated using a spatially varying mean and variance procedure, are used for image segmentation. The experimental results indicate the effectiveness of the method.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Barcelos, C. , Chen, Y. and Chen, F. (2014) Soft Image Segmentation Based on the Mixture of Gaussians and the Phase-Transition Theory. Applied Mathematics, 5, 2888-2898. doi: 10.4236/am.2014.518275.

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