Wesley E. Snyder

Fundamentals of Computer Vision (eBook, ePUB)

• Format: ePub

Produktbeschreibung

Computer vision has widespread and growing application including robotics, autonomous vehicles, medical imaging and diagnosis, surveillance, video analysis, and even tracking for sports analysis. This book equips the reader with crucial mathematical and algorithmic tools to develop a thorough understanding of the underlying components of any complete computer vision system and to design such systems. These components include identifying local features such as corners or edges in the presence of noise, edge preserving smoothing, connected component labeling, stereopsis, thresholding, clustering, segmentation, and describing and matching both shapes and scenes. The extensive examples include photographs of faces, cartoons, animal footprints, and angiograms, and each chapter concludes with homework exercises and suggested projects. Intended for advanced undergraduate and beginning graduate students, the text will also be of use to practitioners and researchers in a range of applications.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 28. September 2017
• Englisch
• ISBN-13: 9781316884959
• Artikelnr.: 49264190

Autorenporträt

Wesley E. Snyder is Professor Emeritus of Electrical and Computer Engineering at North Carolina State University. He was previously a professor at the Bowman Gray School of Medicine and worked at the GE Corporate Research and Development Center, NASA Langley Research Center, and the West German Air and Space Agency (DLR). He has published 179 research papers and was chosen as an Outstanding Engineering Educator in North Carolina in 1993. He was made fellow of the Institute of Electrical and Electronics Engineers (IEEE), Gladden Fellow (University of Western Australia), and Fellow of the American Institute of Medical and Biomedical Engineering.

Inhaltsangabe

Part I. Preliminaries: 1. Computer vision, some definitions, and some history
2. Writing programs to process images
3. Review of mathematical principles
4. Images - representation and creation
Part II. Preprocessing: 5. Kernel operators
6. Noise removal
7. Mathematical morphology
Part III. Image Understanding: 8. Segmentation
9. Parametric transforms
10. Representing and matching shape
11. Representing and matching scenes
Part IV. The 2-D Image in a 3-D World: 12. Relating to three dimensions
13. Developing computer vision algorithms.