Table of Contents

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.

About the Author

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. 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.

Reviews

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.