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Machine Vision
Theory, Algorithms, Practicalities
- 3rd Edition - December 22, 2004
- Author: E. R. Davies
- Language: English
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 4 7 3 2 4 - 6
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… Read more
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Request a sales quoteIn 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.
· 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.
· 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.
Academic and industry researchers in computer science and computer engineering particularly in machine vision, computer vision, and robotics.
About the Author
Dedication
Foreword
Preface
Acknowledgments
Chapter 1: Vision, the Challenge
Part 1: Low-Level Vision
Images and Imaging Operations
Chapter 2: Images and Imaging Operations
Basic Image Filtering Operations
Chapter 3: Basic Image Filtering Operations
Thresholding Techniques
Chapter 4: Thresholding Techniques
Edge Detection
Chapter 5: Edge Detection
Binary Shape Analysis
Chapter 6: Binary Shape Analysis
Boundary Pattern Analysis
Chapter 7: Boundary Pattern Analysis
Mathematical Morphology
Chapter 8: Mathematical Morphology
Part 2: Intermediate-Level Vision
Line Detection
Chapter 9: Line Detection
Circle Detection
Chapter 10: Circle Detection
The Hough Transform and Its Nature
Chapter 11: The Hough Transform and Its Nature
Ellipse Detection
Chapter 12: Ellipse Detection
Hole Detection
Chapter 13: Hole Detection
Polygon and Corner Detection
Chapter 14: Polygon and Corner Detection
Abstract Pattern Matching Techniques
Chapter 15: Abstract Pattern Matching Techniques
Part 3: 3-D Vision and Motion
The Three-Dimensional World
Chapter 16: The Three-Dimensional World
Tackling the Perspective n-point Problem
Chapter 17: Tackling the Perspective n-point Problem
Motion
Chapter 18: Motion
Invariants and Their Applications
Chapter 19: Invariants and Their Applications
Egomotion and Related Tasks
Chapter 20: Egomotion and Related Tasks
Image Transformations
Chapter 21: Image Transformations and Camera Calibration
Part 4: Toward Real-Time Pattern Recognition Systems
Automated Visual Inspection
Chapter 22: Automated Visual Inspection
Inspection of Cereal Grains
Chapter 23: Inspection of Cereal Grains
Statistical Pattern Recognition
Chapter 24: Statistical Pattern Recognition
Biologically Inspired Recognition Schemes
Chapter 25: Biologically Inspired Recognition Schemes
Texture
Chapter 26: Texture
Image Acquisition
Chapter 27: Image Acquisition
Real-Time Hardware and Systems Design Considerations
Chapter 28: Real-Time Hardware and Systems Design Considerations
Part 5: Perspectives on Vision
Chapter 29: Machine Vision: Art or Science?
Robust Statistics
Appendix A: Robust Statistics
List of Acronyms and Abbreviations
References
Author Index
Subject Index
- No. of pages: 934
- Language: English
- Edition: 3
- Published: December 22, 2004
- Imprint: Morgan Kaufmann
- eBook ISBN: 9780080473246
ED
E. R. Davies
Roy Davies is Emeritus Professor of Machine Vision at Royal Holloway, University of London. He has worked on many aspects of vision, from feature detection to robust, real-time implementations of practical vision tasks. His interests include 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 holds a DSc at the University of London, and has been awarded Distinguished Fellow of the British Machine Vision Association, and Fellow of the International Association of Pattern Recognition.
Affiliations and expertise
Emeritus Professor of Machine Vision, Royal Holloway, University of London, UKRead Machine Vision on ScienceDirect