Computer and Machine Vision: Theory, Algorithms, Practicalities

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Academic Press, Apr 18, 2012 - Technology & Engineering - 912 pages
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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


  • 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
 

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Contents

1 Vision the Challenge
1
1 LowLevel Vision
15
2 IntermediateLevel Vision
227
3 3D Vision and Motion
387
4 Toward RealTime Pattern Recognition Systems
523
Appendix A Robust Statistics
778
References
796
Author Index
845
Subject Index
861
Color Plates
872
Copyright

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About the author (2012)

Roy Davies is a Professor of Machine Vision at Royal Holloway, University of London, and has extensive experience of machine vision, image analysis, automated visual inspection, and noise suppression techniques. His book Electronics, Noise, and Signal Recovery was published in 1993 by Academic Press, and is a useful companion to the present volume.

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