This robust text provides deep and wide coverage of the full range of topics encountered in the field of image processing and machine vision. As a result, it can serve undergraduates, graduates, researchers, and professionals looking for a readable reference. The book's encyclopedic coverage of topics is wider than that found in any competing book, and it can be used in more than one course (both image processing and machine vision classes). In addition, while advanced mathematics is not needed to understand basic concepts (making this a good choice for undergraduates), rigorous mathematical coverage is included for more advanced readers. This text is especially strong and up-to-date in its treatment of 3D vision, with many topics not covered at all in competing books. It is also distinguished by its easy-to-understand algorithm descriptions of difficult concepts, and a wealth of carefully selected problems and examples that can be worked with any general-purpose image processing software package or programming environment.

About the Authors

Milan Sonka is Professor of Electrical and Computer Engineering at the University of Iowa. His research interests include medical image analysis, computer-aided diagnosis, and machine vision.

Vaclav Hlavac is Professor of Cybernetics at the Czech Technical University, Prague. his research interests are knowledge based image analysis, 3D model-based vision and relations between statistical and structural pattern recognition.

Roger Boyle is Professor Emeritus of Computing and was Head of the School of Computing at the University of Leeds, England where his research interests are low-level vision and pattern recognition.

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