• Computer and Machine Vision; Theory, Algorithms, Practicalities (Hardback) 9780123869081
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Computer and Machine Vision
Theory, Algorithms, Practicalities

Learn not just the principles of machine and computer vision but the ‘ins and outs’ of developing real-world applications!

E. R. Davies (Author)

9780123869081, Elsevier Science

Hardback, published 18 April 2012

912 pages
23.4 x 19 x 4.4 cm, 1.7 kg

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 constraints. This fully revised fourth edition has brought in more of the concepts and applications of computer vision, making it a very comprehensive and up-to-date tutorial text suitable for graduate students, researchers and R&D engineers working in this vibrant subject.

Key features include:

  • Practical examples and case studies give the ‘ins and outs’ of developing real-world vision systems, giving engineers the realities of implementing the principles in practice
  • New chapters containing case studies on surveillance and driver assistance systems give practical methods on these cutting-edge applications in computer vision
  • Necessary mathematics and essential theory are made approachable by careful explanations and well-illustrated examples
  • Updated content and new sections cover topics such as human iris location, image stitching, line detection using RANSAC, performance measures, and hyperspectral imaging
  • The ‘recent developments’ section now included in each chapter will be useful in bringing students and practitioners up to date with the subject

1. Vision, the Challenge2. Images and Imaging Operations3. Basic Image Filtering Operations4. Thresholding Techniques5. Edge Detection6. Corner and Interest Point Detection7. Mathematical Morphology8. Texture9. Binary Shape Analysis10. Boundary Pattern Analysis11. Line Detection12. Circle and Ellipse Detection13. The Hough Transform and Its Nature14. Abstract Pattern Matching Techniques15. The Three-Dimensional World16. Tackling the perspective n-point problem17. Invariants and perspective18. Image transformations and camera calibration19. Motion20. Automated Visual Inspection21. Inspection of Cereal Grains22. Surveillance23. In-Vehicle Vision Systems24 Statistical Pattern Recognition25. Image Acquisition26. Real-Time Hardware and Systems Design Considerations27. Epilogue - Perspectives in VisionAppendix Robust statistics

Subject Areas: Network management [UTF], Communications engineering / telecommunications [TJK], Electronics & communications engineering [TJ], Engineering: general [TBC]
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