Texture analysis is one of the fundamental aspects of human vision by which we discriminate between surfaces and objects. In a similar manner, computer vision can take advantage of the cues provided by surface texture to distinguish and recognize objects. In computer vision, texture analysis may be used alone or in combination with other sensed features (e.g. color, shape, or motion) to perform the task of recognition. Either way, it is a feature of paramount importance and boasts a tremendous body of work in terms of both research and applications.Currently, the main approaches to texture analysis must be sought out through a variety of research papers. This collection of chapters brings together in one handy volume the major topics of importance, and categorizes the various techniques into comprehensible concepts. The methods covered will not only be relevant to those working in computer vision, but will also be of benefit to the computer graphics, psychophysics, and pattern recognition communities, academic or industrial.
Introduction to Texture Analysis (R Davies); Texture Modeling and Synthesis (R Paget); Local Statistical Operators for Texture Classification (M Varma & A Zisserman); Texems: Random Texture Representation and Analysis (X Xie & M Mirmehdi); Color Texture Analysis (P Whelan & O Ghita); 3D Texture Analysis (M Chantler & M Petrou); Shape, Surface Roughness and Human Perception (S Pont & J Koenderink); Texture for Appearance Models in Computer Vision and Graphics (O Cula & K Dana); From Dynamic Texture to Dynamic Shape and Appearance Models: An Overview (G Doretto & S Soatto); Divide-and-Texture: Hierarchical Texture Description (G Caenen et al.); Case Study 1: A Tutorial on the Practical Implementation of the Trace Transform (M Petrou & F Wang); Case Study 2: Face Analysis Using Local Binary Patterns (A Hadid et al.); A Galaxy of Texture Features (X Xie & M Mirmehdi).