This textbook can be used for an undergraduate course in digital image processing and analysis, or an undergraduate/graduate course in computer vision. The updated version presents new sections on compression via JPEG and MPEG, fractals, fuzzy logic recognition, hidden Markov models, Kalman filters
"synopsis" may belong to another edition of this title.
Vision allows humans to perceive and understand the world surrounding them; computer vision aims to duplicate human vision by electronically perceiving and understanding an image. Image Processing, Analysis and Machine Vision is a comprehensive introduction to the field providing up-to-date coverage of all aspects of the subject. This book reflects the authors' experience in teaching one and two semester undergraduate and graduate courses in Digital Image Processing, Digital Image Analysis, Machine Vision and Intelligent Robotics, it is also influenced by their active research in these area. Many algorithms, diagrams, examples and up-to-date references make this book required reading for students and professionals involved in computer vision.
This textbook can be used for an undergraduate course in digital image processing and analysis, or an undergraduate/graduate course in computer vision. The updated version presents new sections on compression via JPEG and MPEG, fractals, fuzzy logic recognition, hidden Markov models, Kalman filters
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