Intelligent Machine Vision : Techniques, Implementation and Applications

By: Bruce G. Batchelor, B. G. Batchelor, Frederick Waltz

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Hardcover
454 Pages

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23.5 x 15.88 x 2.54

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Intelligent Machine Vision: Techniques, Implementations & Applications brings together the central issues involved in this exciting and topical subject.
Drawing on half a century of combined experience, the authors describe state of the art and the latest developments in the field, including:
- fundamentals of 'intelligent' image processing, specifically intended for Machine Vision systems;
- algorithm optimization;
- implementation in high-speed electronic digital hardware;
- implementation in an integrated high-level software environment;
- applications for industrial product quality and process control.
There are hundreds of illustrations in the book, most of them created using the author's 'PIP' software - a sophisticated intelligent image processing package.
A demonstration version of this software, as well as numerous examples from the book, are available at the authors' Web site: http: //bruce.cs.cf.ac.uk/bruce/index.html

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Non-Fiction Computing & I.T.Computer Science Image Processing Artificial Intelligence Computer Vision Engineering & Technology Other Technologies & Applied Sciences Applied Optics Graphical & Digital Media Applications Computer Networking & Communications

Contents
Preface
Acknowledgments
Glossary of terms, products, and acronyms
Software and hardware availability
Machine vision for industrial applications	p. 1
Natural and artificial vision	p. 1
Artificial vision	p. 3
Machine Vision is not Computer Vision	p. 6
Four case studies	p. 12
Machine Vision is engineering, not science	p. 17
Structure, design, and use of machine vision systems	p. 18
Other design tools	p. 23
Outline of this book	p. 27
Basic machine vision techniques	p. 31
Representations of images	p. 31
Elementary image-processing functions	p. 33
Binary images	p. 42
Binary mathematical morphology	p. 49
Grey-scale morphology	p. 53
Global image transforms	p. 55
Texture analysis	p. 58
Further remarks	p. 63
Algorithms, approximations, and heuristics	p. 65
Introduction	p. 65
Changing image representation	p. 75
Redefining algorithms	p. 82
Approximate and heuristic methods	p. 108
Additional remarks	p. 129
Systems engineering	p. 135
Interactive and target vision systems	p. 135
Interactive vision systems, general principles	p. 136
Prolog image processing (PIP)	p. 144
Advanced aspects of PIP	p. 171
Windows image processing (WIP)	p. 196
Web-based image processing (CIP)	p. 198
Target (factory floor) vision systems	p. 201
Concluding remarks	p. 202
Algorithms and architectures for fast execution	p. 203
Classification of operations	p. 203
Implementation of monadic pixel-by-pixel operations	p. 204
Implementation of dyadic pixel-by-pixel operations	p. 205
Implementation of monadic neighbourhood operations	p. 207
Implementation of monadic global operations	p. 209
SKIPSM - a powerful implementation paradigm	p. 211
Image-processing architectures	p. 218
Systems with random access to image memory	p. 219
Systems with sequential image memory access only	p. 224
Systems for continuous web-based processing	p. 228
Adding intelligence	p. 231
Preliminary remarks	p. 231
Implementing image-processing operators	p. 234
Very Simple Prolog+ (VSP)	p. 238
PIP	p. 251
WIP	p. 265
Concluding remarks	p. 271
Vision systems on the Internet	p. 273
Stand-alone and networked systems	p. 273
Java	p. 274
Remotely-Operated Prototyping Environment (ROPE)	p. 278
CIP	p. 288
Remarks	p. 293
Visual programming for machine vision	p. 295
Design outline	p. 295
Data types	p. 300
Nonlinear feedback blocks	p. 302
Visual programming environment	p. 305
Image viewer and tools	p. 309
Sample problems	p. 311
Summary	p. 315
Application case studies	p. 317
Preliminary remarks	p. 317
Taking a broad view	p. 318
Cracks in ferrous components	p. 324
Aerosol spray cone	p. 325
Glass vial	p. 326
Coin	p. 327
Metal grid	p. 328
Toroidal metal component	p. 329
Mains power plug (X-ray)	p. 331
Conclusions	p. 332
Final remarks	p. 335
Interactive prototyping systems	p. 336
Target vision systems	p. 337
Design tools	p. 339
Networked systems	p. 340
Systems integration	p. 341
Algorithms and heuristics	p. 342
Concluding comments	p. 343
Programmable color filter	p. 345
A brief introduction to Prolog	p. 353
PIP commands and their implementation	p. 361
References	p. 369
Futher reading	p. 374
Index	p. 377
Table of Contents provided by Blackwell. All Rights Reserved.

Intelligent Machine Vision : Techniques, Implementation and Applications

At a Glance

Hardcover

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