In computer vision application texture analysis plays an important role same as Artificial Intelligence plays in classification and decision making. Better texture feature gives better results while classification even the accuracy of classifier is totally depend on the type and values variations of features. Different methods for digital-image texture analysis like Structural, Statistical, Model–Based and Transform based are reviewed based on available literature and research work either carried out or supervised by the authors. Different texture databases available online is also discussed with their characteristics and the best texture feature which can describe the database well. The paper is concluded with texture features which can describe variation in given image.