A Survey on Texture Image Descriptors in Computer Vision Applications

In computer vision, the texture is defined as a function of spatial variation of the intensity of the pixels in the whole image. Texture is one of the main terms used to define objects or concepts of a given image. It is used along with color and shape to describe image contents. Texture analysis plays an important role in computer vision and image processing cases such as medical diagnosis, object recognition, defect detection, visual pattern recognition, noise reduction, etc. Until now different approaches have been proposed to analysis texture images. Texture analysis methods usually are classified into four categories: statistical methods, structural, model-based and transform- based methods. In this paper, the various applications of texture analysis methods are discussed in details. The common step of many computer vision applications is feature extraction. Texture features are so discriminative in many cases. A comparisons study of different texture descriptors is proposed in terms of using variety