Book 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.· 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.
Table of contents
- Cover image
- Title page
- Table of Contents
- Machine Vision
- About the Author
- Copyright
- 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
- Appendix A: Robust Statistics
- List of Acronyms and Abbreviations
- References
- Author Index
- Subject Index
Product information
- Title: Machine Vision, 3rd Edition
- Author(s):
- Release date: December 2004
- Publisher(s): Morgan Kaufmann
- ISBN: 9780080473246
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