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Machine Vision

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

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Machine Vision
  5. About the Author
  6. Copyright
  7. Dedication
  8. Foreword
  9. Preface
  10. Acknowledgments
  11. Chapter 1: Vision, the Challenge
  12. Part 1: Low-Level Vision
    1. Images and Imaging Operations
    2. Chapter 2: Images and Imaging Operations
    3. Basic Image Filtering Operations
    4. Chapter 3: Basic Image Filtering Operations
    5. Thresholding Techniques
    6. Chapter 4: Thresholding Techniques
    7. Edge Detection
    8. Chapter 5: Edge Detection
    9. Binary Shape Analysis
    10. Chapter 6: Binary Shape Analysis
    11. Boundary Pattern Analysis
    12. Chapter 7: Boundary Pattern Analysis
    13. Mathematical Morphology
    14. Chapter 8: Mathematical Morphology
  13. Part 2: Intermediate-Level Vision
    1. Line Detection
    2. Chapter 9: Line Detection
    3. Circle Detection
    4. Chapter 10: Circle Detection
    5. The Hough Transform and Its Nature
    6. Chapter 11: The Hough Transform and Its Nature
    7. Ellipse Detection
    8. Chapter 12: Ellipse Detection
    9. Hole Detection
    10. Chapter 13: Hole Detection
    11. Polygon and Corner Detection
    12. Chapter 14: Polygon and Corner Detection
    13. Abstract Pattern Matching Techniques
    14. Chapter 15: Abstract Pattern Matching Techniques
  14. Part 3: 3-D Vision and Motion
    1. The Three-Dimensional World
    2. Chapter 16: The Three-Dimensional World
    3. Tackling the Perspective n-point Problem
    4. Chapter 17: Tackling the Perspective n-point Problem
    5. Motion
    6. Chapter 18: Motion
    7. Invariants and Their Applications
    8. Chapter 19: Invariants and Their Applications
    9. Egomotion and Related Tasks
    10. Chapter 20: Egomotion and Related Tasks
    11. Image Transformations
    12. Chapter 21: Image Transformations and Camera Calibration
  15. Part 4: Toward Real-Time Pattern Recognition Systems
    1. Automated Visual Inspection
    2. Chapter 22: Automated Visual Inspection
    3. Inspection of Cereal Grains
    4. Chapter 23: Inspection of Cereal Grains
    5. Statistical Pattern Recognition
    6. Chapter 24: Statistical Pattern Recognition
    7. Biologically Inspired Recognition Schemes
    8. Chapter 25: Biologically Inspired Recognition Schemes
    9. Texture
    10. Chapter 26: Texture
    11. Image Acquisition
    12. Chapter 27: Image Acquisition
    13. Real-Time Hardware and Systems Design Considerations
    14. Chapter 28: Real-Time Hardware and Systems Design Considerations
  16. Part 5: Perspectives on Vision
    1. Chapter 29: Machine Vision: Art or Science?
    2. Robust Statistics
  17. Appendix A: Robust Statistics
  18. List of Acronyms and Abbreviations
  19. References
  20. Author Index
  21. Subject Index