Machine Vision
eBook - PDF

Machine Vision

Theory, Algorithms, Practicalities

  1. 572 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Machine Vision

Theory, Algorithms, Practicalities

About this book

Machine Vision: Theory, Algorithms, Practicalities covers the limitations, constraints, and tradeoffs of vision algorithms. This book is organized into four parts encompassing 21 chapters that tackle general topics, such as noise suppression, edge detection, principles of illumination, feature recognition, Bayes' theory, and Hough transforms. Part 1 provides research ideas on imaging and image filtering operations, thresholding techniques, edge detection, and binary shape and boundary pattern analyses. Part 2 deals with the area of intermediate-level vision, the nature of the Hough transform, shape detection, and corner location. Part 3 demonstrates some of the practical applications of the basic work previously covered in the book. This part also discusses some of the principles underlying implementation, including on lighting and hardware systems. Part 4 highlights the limitations and constraints of vision algorithms and their corresponding solutions. This book will prove useful to students with undergraduate course on vision for electronic engineering or computer science.

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Table of contents

  1. Front Cover
  2. Machine Vision: Theory, Algorithms, Practicalities
  3. Copyright Page
  4. Preface
  5. Acknowledgements
  6. Table of Contents
  7. Chapter 1. Vision, the Challenge
  8. Part-1 Low-Level Processing
  9. Chapter 2. Images and Imaging Operations
  10. Chapter 3. Basic Image Filtering Operations
  11. Chapter 4. Thresholding Techniques
  12. Chapter 5. Locating Objects via Their Edges
  13. Chapter 6. Binary Shape Analysis
  14. Chapter 7. Boundary Pattern Analysis
  15. Part-2 Intermediate-Level Processing
  16. Chapter 8. Line Detection
  17. Chapter 9. Circle Detection
  18. Chapter 10. The Hough Transform and Its Nature
  19. Chapter 11. Ellipse Detection
  20. Chapter 12. Polygon Detection
  21. Chapter 13. Hole Detection
  22. Chapater 14. Corner Location
  23. Part-3 Application-Level Processing
  24. Chapter 15. Abstract Pattern Matching Techniques
  25. Chapter 16. The Three-Dimensional World
  26. Chapter 17. Automated Visual Inspection
  27. Chapter 18. Statistical Pattern Recognition
  28. Chapter 19. Image Acquisition
  29. Chapter 20. The Need for Speed: Real-Time Electronic Hardware Systems
  30. Part-4 Perspectives on Vision
  31. Chapter 21. Machine Vision, Art or Science?
  32. Appendix: Programming Notation
  33. References
  34. Subject Index
  35. Author Index

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Yes, you can access Machine Vision by E. R. Davies, P. G. Farrell,J. R. Forrest in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Science General. We have over one million books available in our catalogue for you to explore.