基于马尔可夫随机场的图像分割方法研究

摘要

在计算机视觉和图像处理等相关领域的Markov（Markov Random Field,即马尔可夫随机场）引入概率这个概念后可以很好地描述图像中各像素间由于处于不同位置而形成的一些特性.主要研究了基于MRF的一种模型——条件随机场CRFs（Conditional Random Fields）模型及其在图像分割中的应用.%The theory of Markov Random Field（MRF） has now been widely used in the computer vision and image processing,it is mainly used by a relatively convenient way to describe the probability of pixels between each image has the number of space-related features.In this paper we mainly studied one model based on MRF——the Conditional Random Fields（CRFs） and its application in image segmentation.