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. Key Features • Covers some of the most important and popular approaches to automatic texture analysis while simultaneously introducing new concepts • Is aimed at the general cross-section of the academic and industrial community involved in research in texture analysis • Will appeal to postgraduate research students, postdoctorate research assistants, and full-time faculty academics involved in texture analysis; as well as research scientists working in companies involved in developing image analysis and computer vision software, such as companies whose business involves security and surveillance using CCTV images, product quality inspection, medical imaging, etc. • Serves as a “bible” on texture analysis for computer vision practitioners

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