Concrete CT Image Segmentation method based on Markov Random Field

The article based on Markov Random Field (MRF) image segmentation model and beyes theory, the segmentation issue is transformed to the Maximum A Posteriori (MAP). The forecast of parameter arithmetic is provide. The article proposed a modified version of the metropolis dynamics (MMD) simulated annealing arithmetic. Experimental results are compared to those obtained by the Metropolis algorithm, the Gibbs sampler and ICM (Iterated Conditional Mode). The efficiency and precision is more improve. Using MMD on Concrete CT Image Segmentation can reflect the interior spatial distribution of the concrete materials on deformation, and afford an effective method on concrete meso-structure CT image study on Architecture projection.