Machine Vision, Volume 1

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Cambridge University Press, Jan 8, 2004 - Computers - 434 pages
This 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

Introduction
1
Review of mathematical principles
8
Writing programs to process images
29
Formation and representation
38
Linear operators and kernels
65
Topic 5A Edge detectors
97
Restoration and feature extraction
107
Topic 6A Alternative and equivalent algorithms
129
Consistent labeling
263
Topic 10A 3D Interpretation of 2D line drawings
271
Graphs and graphtheoretic concepts
290
Image matching
298
Topic 13A Matching
312
Statistical pattern recognition
326
Topic 14A Statistical pattern recognition
347
Clustering
356

Mathematical morphology
144
Topic 7A Morphology
158
Segmentation
181
Topic 8A Segmentation
207
Shape
216
Topic 9A Shape description
240
Syntactic pattern recognition
369
Applications
382
Automatic target recognition
392
Author index
417
Index
426
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About the author (2004)

Hairong Qi received her PhD from North Carolina State University and is currently an Assistant Professor of Electrical and Computer Engineering at the University of Tennessee, Knoxville.