GMM-HMRF
GMM-HMRF
Overview
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.
This library is also available on MathWorks:
Citations
If you use this library, please cite:
@article{wang2012gmm,
title={GMM-based hidden Markov random field for color image and 3D volume segmentation},
author={Wang, Quan},
journal={arXiv preprint arXiv:1212.4527},
year={2012}
}
Citation pour cette source
Quan Wang (2024). GMM-HMRF (https://github.com/wq2012/GMM-HMRF/releases/tag/v1.2), GitHub. Récupéré le .
Compatibilité avec les versions de MATLAB
Plateformes compatibles
Windows macOS LinuxCatégories
- Image Processing and Computer Vision > Image Processing Toolbox > 3-D Volumetric Image Processing >
- Image Processing and Computer Vision > Image Processing Toolbox > Image Segmentation and Analysis > Image Segmentation >
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code/color-image
code/three-dimensional
Version | Publié le | Notes de version | |
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1.2 | See release notes for this release on GitHub: https://github.com/wq2012/GMM-HMRF/releases/tag/v1.2 |
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1.1.0.0 | Rewrote some minor parts in C++. |
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1.0.0.0 |