Machine Vision, Volume 1This book is an accessible and comprehensive introduction to machine vision. It provides all the necessary theoretical tools and shows how they are applied in actual image processing and machine vision systems. A key feature is the inclusion of many programming exercises that give insights into the development of practical image processing algorithms. A CD-ROM containing software and data used in these exercises is included. The book is aimed at graduate students in electrical engineering, computer science, and mathematics. It will also be a useful reference for practitioners. |
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Contents
Review of mathematical principles | 8 |
Writing programs to process images | 30 |
Formation and representation | 46 |
5 | 53 |
Linear operators and kernels | 65 |
10 | 70 |
5 | 75 |
28 | 78 |
Topic 8A Segmentation | 207 |
Shape | 216 |
Topic 9A Shape description | 240 |
Consistent labeling | 263 |
Parametric transforms | 275 |
Graphs and graphtheoretic concepts | 290 |
Image matching | 298 |
Topic 13A Matching | 312 |
10 | 85 |
Topic 5A Edge detectors | 97 |
38 | 98 |
Restoration and feature extraction | 107 |
4 | 115 |
Topic 6A Alternative and equivalent algorithms | 129 |
Mathematical morphology | 144 |
Topic 7A Morphology | 158 |
Segmentation | 181 |
Statistical pattern recognition | 326 |
Topic 14A Statistical pattern recognition | 347 |
Clustering | 356 |
Syntactic pattern recognition | 369 |
Applications | 382 |
Automatic target recognition | 392 |
417 | |
426 | |
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