in recent years, some statisticians have studied the signal detection problem by using the random field theory. in this paper we have considered point estimation of the gaussian scale space random field parameters in the bayesian approach. since the posterior distribution for the parameters of interest dose not have a closed form, we introduce the markov chain monte carlo (mcmc) algorithm to ap...

image segmentation is an important task in image processing and computer vision which attract many researchers attention. there are a couple of information sets pixels in an image: statistical and structural information which refer to the feature value of pixel data and local correlation of pixel data, respectively. markov random field (mrf) is a tool for modeling statistical and structural inf...

We study how the typical gradient and height of a random surface are modified by addition quenched disorder in form independent external field. The results provide quantitative estimates, sharp up to multiplicative constants, following cases. It is shown that for real-valued random-field surfaces $$\nabla \phi $$ type with uniformly convex interaction potential: (i) delocalizes dimensions $$1\l...

• Present modeling abstraction that we call random field optimization. Abstraction captures uncertainty lives on continuous space-time domains. Demonstrate the applicability using case studies. We present a new paradigm for optimization Random fields are powerful aims to capture behavior of variables live infinite-dimensional spaces (e.g., space and time) such as stochastic processes time serie...

texture image analysis is one of the most important working realms of image processing in medical sciences and industry. up to present, different approaches have been proposed for segmentation of texture images. in this paper, we offered unsupervised texture image segmentation based on markov random field (mrf) model. first, we used gabor filter with different parameters’ (frequency, orientatio...

one of the main distinctions between geomaterials and other engineering materials is the spatial variation of their properties in different directions. this characteristic of geomaterials -so called heterogeneity- is studied herewith. several spatial distributions are introduced to describe probabilistic variation of geotechnical properties of soils. among all, the absolute normal distribution ...

the purpose of this study is to compare the results of different probabilistic methods such as the perturbation method, stochastic finite element method (sfem) and monte carlo method. these methods were used to study the convergence of direct approach for slope stability analysis and are developed for a linear soil behavior. in this study, two dimensional random fields are used and both the fir...