Image Processing, Analysis, and Machine Vision, 4/E
The brand new edition of IMAGE PROCESSING, ANALYSIS, AND MACHINE VISION is a robust text providing 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 wide, 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. It is also distinguished by its easy-to-understand algorithm descriptions of difficult concepts, and a wealth of carefully selected problems and examples.FeaturesEach chapter is supported by an extensive list of references and exercises.A selection of algorithms is summarized and presented formally in a manner that should aid implementation.Reflects the authors'' experience in teaching one and two semester undergraduate courses in Digital Image Processing, Digital Image Analysis, Image Understanding, Medical Imaging, Machine Vision, Pattern Recognition, and Intelligent Robotics at their respective institutions.Each chapter further includes a concise Summary section.A suggestion for partitioning the contents with possible course outlines is included in the books front matter.A full set of PowerPoint slides is available for download from this site -- PowerPoints include all images and chapter summaries from the text.
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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. 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. 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.
List of Algorithms. Preface. Possible Course Outlines. 1. Introduction. 2. The Image, Its Representations and Properties. 3. The Image, Its Mathematical and Physical Background. 4. Data Structures for Image Analysis. 5. Image Pre-Processing. 6. Segmentation I. 7. Segmentation II. 8. Shape Representation and Description. 9. Object Recognition. 10. Image Understanding. 11. 3d Geometry, Correspondence, 3d from Intensities. 12. Reconstruction from 3d. 13. Mathematical Morphology. 14. Image Data Compression. 15. Texture. 16. Motion Analysis. Index.
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Condition: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1500grams, ISBN:9781133593690. Seller Inventory # 9972740
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Seller: Anybook.com, Lincoln, United Kingdom
Condition: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1500grams, ISBN:9781133593690. Seller Inventory # 9972741
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