Computer and machine vision : theory, algorithms, practicalities /

"Computer and Machine Vision: Theory, Algorithms, Practicalities (previously entitled Machine Vision) clearly and systematically presents the basic methodology of computer and machine vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constr...

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Bibliographic Details
Main Author:	Davies, E. R. (Author)
Format:	Electronic eBook
Language:	English
Published:	Waltham, Mass. : Elsevier, 2012.
Edition:	4th ed.
Subjects:	Computer vision. Information visualization.
Online Access:	CONNECT CONNECT

Table of Contents:

Chapter 1. Vision, the Challenge
Part 1. Low-level Vision
Chapter 2. Images and Imaging Operations
Chapter 3. Basic Image Filtering Operations
Chapter 4. Thresholding Techniques
Chapter 5. Edge Detection
Chapter 6. Corner and Interest Point Detection
Chapter 7. Mathematical Morphology
Chapter 8. Texture.
Part 2. Intermediate-level Vision
Chapter 9. Binary Shape Analysis
Chapter 10. Boundary Pattern Analysis
Chapter 11. Line Detection
Chapter 12. Circle and Ellipse Detection
Chapter 13. The Hough Transform and Its Nature
Chapter 14. Pattern Matching Techniques.
Part 3. 3-D Vision and Motion
Chapter 15. The Three-Dimensional World
Chapter 16. Tackling the Perspective n-point Problem
Chapter 17. Invariants and Perspective
Chapter 18. Image Transformations and Camera Calibration
Chapter 19. Motion.
Part 4. Toward Real-time Pattern Recognition Systems
Chapter 20. Automated Visual Inspection
Chapter 21. Inspection of Cereal Grains
Chapter 22. Surveillance
Chapter 23. In-Vehicle Vision Systems
Chapter 24. Statistical Pattern Recognition
Chapter 25. Image Acquisition
Chapter 26. Real-Time Hardware and Systems Design Considerations
Chapter 27. Epilogue--Perspectives in Vision
Appendix A. Robust Statistics.

Computer and machine vision : theory, algorithms, practicalities /

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