Based on Modified Metropolis Dynamics Concrete CT Image Classification

In recent years, the architecture quality problem has been getting more and more attention. Concrete is a sort of savageness disfigurement material and is abroad in architecture industry. But concrete meso-structure has not been more analyzed. In this paper, we present a pseudo-stochastic variation of the Metropolis dynamics for combinatorial optimization in concrete CT image classification using Markov Random Fields. Experimental results are compared to those obtained by the Metropolis algorithm, the Gibbs sampler and ICM (Iterated Conditional Mode). Classify result indicate that using MMD can reflect the interior spatial distribution of the concrete materials on deformation, and afford an effective method on concrete meso-structure CT image study.