This books equips the advanced undergraduate or graduate student with crucial mathematical and algorithmic tools to develop computer software which can analyze images and produce decisions about the content of those images. Examples include identification and measurement of regions in medical images as well as defects in manufactured products.
This books equips the advanced undergraduate or graduate student with crucial mathematical and algorithmic tools to develop computer software which can analyze images and produce decisions about the content of those images. Examples include identification and measurement of regions in medical images as well as defects in manufactured products.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.
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.
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