| Preface (2006) | |||||||||||||||
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| Angeles. It is also being taught by Andrès Almansa at the Facultad de Ingeneria, Montevideo. This text will be of interest to several kinds of audiences. Our teaching experience proves that specialists in image analysis and computer vision find the text easy on the computer vision side and accessible on the mathematical level. The prerequisites are elementary calculus and probability from the first two undergraduate years of any science course. All slightly more advanced notions in probability (inequalities, stochastic geometry, large deviations...) will be either proved in the text or detailed in several exercises at the end of each chapter. We have always asked the students to do all exercises and they usually succeed no matter what their science background is. The mathematics students don’t find the mathematics difficult and easily learn through the text itself what is needed in vision psychology and the practice of computer vision. The text aims at being self-contained in all three aspects: mathematics, vision and algorithms. We shall in particular explain what a digital image is and how the elementary structures can be computed. We wish to emphasize why we are publishing these notes in a mathematics collection. The main question treated in this course is the visual perception of geometric structure. We | |||||||||||||||
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