The chapter divides main computational approaches to texture analysis into either descriptive or generic and introduces each category separately. In particular, basic concepts, theories and techniques related to Markov-Gibbs random fields (MGRF) are discussed. Two representative MGRF models, namely, auto-models and FRAME model, are introduced in detail. Finally, texture synthesis algorithms by non-parametric sampling are also reviewed.