All Book Download,| Machine Vision | This introduction to the field of computer vision focuses on basic concepts and techniques. The thrust is to give practitioners what they need to know to develop a practical machine vision system. Binary vision, segmentation, constraint propagation techniques are presented as are camera calibration, color and texture, detection of motion, and object recognition. This text is appropriate for use in Computer Science and Electrical Engineering departments at the undergraduate or early graduate level and should be suitable for students with no prior knowledge of computer graphics or signal processing. Students should have a working knowledge of mathematics through calculus of two variables, including matrices and linear spaces, and familiarity with basic probability theory, computer programming, and elementary data structures. Numerical and statistical methods and advanced algorithms are described as needed as well as material on geometry in two and three dimensions.
For some sections in the book, more mathematical background is needed. Such sections can be omitted by readers not interested in the rigorous formalization.
For some sections in the book, more mathematical background is needed. Such sections can be omitted by readers not interested in the rigorous formalization.
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