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.
Table of Contents
List of Algorithms.
Possible Course Outlines.
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.
16. Motion Analysis.