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Machine Vision, Third Edition: Theory, Algorithms, Practicalities (Signal Processing and its Applications), by E. R. Davies
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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.
� Includes solid, accessible coverage of 2-D and 3-D scene analysis.
� Offers thorough treatment of the Hough Transform―a key technique for inspection and surveillance.
� Brings vital topics and techniques together in an integrated system design approach.
� Takes full account of the requirement for real-time processing in real applications.
- Sales Rank: #1798659 in Books
- Published on: 2005-01-05
- Original language: English
- Number of items: 1
- Dimensions: 2.29" h x 7.60" w x 9.62" l, 4.55 pounds
- Binding: Hardcover
- 934 pages
Review
“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
About the Author
Roy Davies is a Professor of Machine Vision at Royal Holloway, University of London, and has extensive experience of machine vision, image analysis, automated visual inspection, and noise suppression techniques. His book Electronics, Noise, and Signal Recovery was published in 1993 by Academic Press, and is a useful companion to the present volume.
Most helpful customer reviews
19 of 19 people found the following review helpful.
Good survey of specific machine vision techniques
By calvinnme
To begin with, the latest edition of this book was published in 2004, so all reviews dated earlier than that are referring to a previous edition. This book is a good one on issues and algorithms as they pertain to machine vision versus general computer vision. If you want a good general textbook on computer vision try "Computer Vision" by Linda Shapiro. It has all of the background material and a firm foundation in all of the topics you would expect in a course on computer vision. This book also has a section on introductory computer vision topics, I just don't think it is as clear and as comprehensive as Shapiro's book, especially for students.
However, if you want an excellent treatment of the kinds of problems specific to machine vision - the detection of lines, holes, corners, circles, elipses, and polygons, for example, along with specific algorithm details, this book is very good. It also has good sections on pattern matching, motion estimation, and 3D machine vision. I would recommend it especially for those individuals who are already familiar with the basics of computer vision and would like a book on algorithms for solving specific problems in machine vision. I notice that Amazon only shows the table of contents for the previous edition, so I show the table of contents for the new edition next:
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 - 3D 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?
5 of 5 people found the following review helpful.
Book with basic techniques
By M.Davydov
It is a good book for beginners in image processing. Basic techniques are well described with mathematical formulas and algorithms. There is a lot of models considering computer vision geometry.
On the other side there is a lack of modern techniques in the book. You will find no info about Haar features, Bayesian fields, Gabor filters. Neural networks, Ada-boost, SVM, PCA are described superficially. You will need more info to implement them.
2 of 2 people found the following review helpful.
Excelent discussion of Machine VIsion and goes in depth into areas often over looked.
By P. Abeles
This book has a bit more of a practical feel than other related books in machine vision/computer vision. I feel it does a good job of balancing mathematics versus practical implementation issues. What I feel makes this book a real gem is how it goes into detail on subjects either glossed over or omitted in other books. Examples of that are its discussion on template based edge detection, various algorithms in Chapter 6: Binary Shape Analysis, corner detection, and a large discussion of the Hough transform (personally I find the Hough transform to be of little value in the images I work with). Recently I have found myself turning to this book more because of the less common information it contains. I tend to get the feel that the author has personally used much of what has been discussed while in other books it often feels like material has been included just because its standard practice to include it. I should note that for the most part I have ignored chapters 16 and beyond that deal with "higher level" vision. There are other books which focus on that area which I use instead.
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