In many types of images including aerial images, biomedical images, satellite images etc., textures play an important role in object and surface identification. It also plays an important role in the fields of pattern recognition and computer vision applications such as image/video retrieval and industrial inspection. It also helps in robot navigation and other applications. Many papers have been published in the field of texture analysis and classification. Traditional methods have assumed that the training and testing inputs are of the same alignment and gray scales. But in practice we come across rotations and gray scale changes, which required new methods. This paper presents a limited and interesting survey of the different texture analysis and classification methods mentioned in the literature. © 2017 Elsevier B.V., All rights reserved.