GMM-Based Hidden Markov Random Field for Color Image and 3D Volume Segmentation

TL;DR

This paper introduces a Gaussian mixture model-based hidden Markov random field algorithm, extending previous models, and applies it to color image and 3D volume segmentation tasks with implementation in MATLAB.

Contribution

It generalizes the HMRF model to Gaussian mixture models and demonstrates its application to complex segmentation problems.

Findings

Effective segmentation of color images achieved

Successful application to 3D volume segmentation

Algorithm implemented in MATLAB for practical use

Abstract

In this project, we first study the Gaussian-based hidden Markov random field (HMRF) model and its expectation-maximization (EM) algorithm. Then we generalize it to Gaussian mixture model-based hidden Markov random field. The algorithm is implemented in MATLAB. We also apply this algorithm to color image segmentation problems and 3D volume segmentation problems.