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Computer Vision Using Local Binary Patterns (Computational Imaging and Vision)

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Humans receive the great majority of information about their environment through sight, and at least 50% of the human brain is dedicated to vision. Vision is also a key component for building artificial systems that can perceive and understand their environment. Computer vision is likely to change society in many ways; for example, it will improve the safety and security of people, it will help blind people see, and it will make human-computer interaction more natural.With computer vision it is possible to provide machines with an ability to understand their surroundings, control the quality of products in industrial processes, help diagnose diseases in medicine, recognize humans and their actions, and search for information from databases using image or video content.

Texture is an important characteristic of many types of images. It can be seen in images ranging from multispectral remotely sensed data to microscopic images. A textured area in an image can be characterized by a nonuniform or varying spatial distribution of intensity or color. The variation reflects some changes in the scene being imaged. For example, an image of mountainous terrain appears textured. In outdoor images, trees, bushes, grass, sky, lakes, roads, buildings etc. appear as different types of texture. The specific structure of the texture depends on the surface topography and albedo, the illumination of the surface, and the position and frequency response of the viewer. An X-ray of diseased tissue may appear textured due to the different absorption coefficients of healthy and diseased cells within the tissue.

Texture can play a key role in a wide variety of applications of computer vision. The traditional areas of application considered for texture analysis include biomedical image analysis, industrial inspection, analysis of satellite or aerial imagery, document image analysis, and texture synthesis for computer graphics or animation.

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