This the MATLAB code that was used to produce the figures and tables in Section V of

F. Forbes and G. Fort, Combining Monte Carlo and mean-field like methods for inference

in Hidden Markov Random Fields, Accepted for publication in IEEE Trans. on Image

Processing, 2006.

1

MATLAB has the capability of running functions written in C. The files which hold the source

for these functions are called MEX-Files. Some functions of our codes are written in C.

The purpose of this software is to implement the MCVEM algorithm, described in the paper

mentioned above, when applied to Image Segmentation. MCVEM consists in combining approximation

techniques - based on variational EM - and simulation techniques - based on MCMC

-.

This software is the first version that is made publicly available.

2 How to

2.1 Obtain the source code

Download it from

http://www.tsi.enst.fr/gfort/INRIA/MCVEM.html

After unpacking the archive, you should obtain

• two-This is the MATLAB code that was used to produce the figures and tables in Section V of

F. Forbes and G. Fort, Combining Monte Carlo and mean-field like methods for inference

in Hidden Markov Random Fields, Accepted for publication in IEEE Trans. on Image

Processing, 2006.

1

MATLAB has the capability of running functions written in C. The files which hold the source

for these functions are called MEX-Files. Some functions of our codes are written in C.

The purpose of this software is to implement the MCVEM algorithm, described in the paper

mentioned above, when applied to Image Segmentation. MCVEM consists in combining approximation

techniques - based on variational EM - and simulation techniques - based on MCMC

-.

This software is the first version that is made publicly available.

2 How to

2.1 Obtain the source code

Download it from

http://www.tsi.enst.fr/gfort/INRIA/MCVEM.html

After unpacking the archive, you should obtain

•　two