
Machine Vision
Theory, Algorithms, Practicalities
E. R. Davies(Author)
Morgan Kaufmann (Publisher)
3rd Edition
Published on 20. January 2005
Book
Hardback
968 pages
978-0-12-206093-9 (ISBN)
Article exhausted; check for reprint
Description
In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications including surveillance, automated inspection, robot assembly, vehicle guidance, traffic monitoring and control, signature verification, biometric measurement, and analysis of remotely sensed images. While researchers and industry specialists continue to document their work in this area, it has become increasingly difficult for professionals and graduate students to understand the essential theory and practicalities well enough to design their own algorithms and systems. This book directly addresses this need.
As in earlier editions, E.R. Davies clearly and systematically presents the basic concepts of the field in highly accessible prose and images, covering essential elements of the theory while emphasizing algorithmic and practical design constraints. In this thoroughly updated edition, he divides the material into horizontal levels of a complete machine vision system. Application case studies demonstrate specific techniques and illustrate key constraints for designing real-world machine vision systems.
As in earlier editions, E.R. Davies clearly and systematically presents the basic concepts of the field in highly accessible prose and images, covering essential elements of the theory while emphasizing algorithmic and practical design constraints. In this thoroughly updated edition, he divides the material into horizontal levels of a complete machine vision system. Application case studies demonstrate specific techniques and illustrate key constraints for designing real-world machine vision systems.
Reviews / Votes
"This book brings together the analytic aspects of image processing with the practicalities of applying the techniques in an industrial setting. It is excellent grounding for a machine vision researcher.? --John Billingsley, University of Southern Queensland"The book in its previous incarnations has established its place as a unique repository of detailed analysis of important image processing and computer vision algorithms. This edition builds on these strengths and adds material to guide the reader's understanding of the latest developments in the field. The result is a comprehensive up-to-date reference text.? --Farzin Deravi, University of Kent
"This book is an essential reference for anyone developing techniques for machine vision analysis, including systems for industrial inspection, biomedical analysis, and much more. It comes from a long-term practitioner and is packed with the fundamental techniques required to build and prototype methods to test their applicability to the problem at hand.? --Majid Mirmehdi, University of Bristol
"The book contains a large number of experimental design and evaluation procedures that are of keen interest to industrial application engineers of machine vision.? --William Wee, University of Cincinnati
"Author E.R. Davies covers essential elements of the theory while addressing algorithmic and practical design constraints. In this updated edition, he divides the material into horizontal levels of a complete machine vision system. He includes coverage of 2-D and 3-D scene analysis, along with the Hough Transform, a key technique for inspection and surveillance.? --Mechanical Engineering, August 2006
More details
Series
Edition
3rd edition
Language
English
Place of publication
San Francisco
United States
Publishing group
Elsevier Science & Technology
Target group
Professional and scholarly
Academic and industry researchers in computer science and computer engineering particularly in machine vision, computer vision, and robotics.
Edition type
New edition
Illustrations
Approx. 400 illustrations
Dimensions
Height: 235 mm
Width: 187 mm
Weight
2080 gr
ISBN-13
978-0-12-206093-9 (9780122060939)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

Book
11/2017
5th Edition
Academic Press
€106.50
Shipment within 15-20 days

Book
04/2012
4th Edition
Academic Press
€94.09
Shipment within 15-20 days
Person
Roy Davies was Emeritus Professor of Machine Vision at Royal Holloway, University of London. He worked on many aspects of vision, from feature detection to robust, real-time implementations of practical vision tasks. His interests included automated visual inspection, surveillance, vehicle guidance, crime detection and neural networks. He has published more than 200 papers, and three books. Machine Vision: Theory, Algorithms, Practicalities (1990) has been widely used internationally for more than 25 years, and is now out in this much enhanced fifth edition. Roy held a DSc at the University of London and was awarded Distinguished Fellow of the British Machine Vision Association, and Fellow of the International Association of Pattern Recognition.
Author
Emeritus Professor of Machine Vision, Royal Holloway, University of London, UK (deceased)
Content
1. Vision, the Challenge
Part 1 Low-Level Vision
2. Images and Imaging Operations
3. Basic Image Filtering Operations
4. Thresholding Techniques
5. Edge Detection
6. Binary Shape Analysis
7. Boundary Pattern Analysis
8. Mathematical Morphology
Part 2 Intermediate-Level Vision
9. Line Detection
10. Circle Detection
11. The Hough Transform and Its Nature
12. Ellipse Detection
13. Hole Detection
14. Polygon and Corner Detection
15. Abstract Pattern Matching Techniques
Part 3 3-D Vision and Motion
16. The Three-Dimensional World
17. Tackling the Perspective n-Point Problem
18. Motion
19. Invariants and their Applications
20. Egomotion and Related Tasks
21. Image Transformations and Camera Calibration
Part 4 Towards Real-Time Pattern Recognition Systems
22. Automated Visual Inspection
23. Inspection of Cereal Grains
24. Statistical Pattern Recognition
25. Biologically Inspired Recognition Schemes
26. Texture
27. Image Acquisition
28. Real-Time Hardware and Systems Design Considerations
Part 5 Perspectives on Vision
29. Machine Vision, Art or Science?
Appendix A Robust Statistics
Part 1 Low-Level Vision
2. Images and Imaging Operations
3. Basic Image Filtering Operations
4. Thresholding Techniques
5. Edge Detection
6. Binary Shape Analysis
7. Boundary Pattern Analysis
8. Mathematical Morphology
Part 2 Intermediate-Level Vision
9. Line Detection
10. Circle Detection
11. The Hough Transform and Its Nature
12. Ellipse Detection
13. Hole Detection
14. Polygon and Corner Detection
15. Abstract Pattern Matching Techniques
Part 3 3-D Vision and Motion
16. The Three-Dimensional World
17. Tackling the Perspective n-Point Problem
18. Motion
19. Invariants and their Applications
20. Egomotion and Related Tasks
21. Image Transformations and Camera Calibration
Part 4 Towards Real-Time Pattern Recognition Systems
22. Automated Visual Inspection
23. Inspection of Cereal Grains
24. Statistical Pattern Recognition
25. Biologically Inspired Recognition Schemes
26. Texture
27. Image Acquisition
28. Real-Time Hardware and Systems Design Considerations
Part 5 Perspectives on Vision
29. Machine Vision, Art or Science?
Appendix A Robust Statistics