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Computer and Machine Vision
 
 

Computer and Machine Vision, 4th Edition

Theory, Algorithms, Practicalities

 
Computer and Machine Vision, 4th Edition,E. R. Davies,ISBN9780123869081
 
 
 

  

Academic Press

9780123869081

9780123869913

912

235 X 191

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

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Key Features

    • 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.

    Description

    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.

    Roy Davies is Emeritus Professor of Machine Vision at Royal Holloway, University of London. He has worked on many aspects of vision, from feature detection to robust, real-time implementations of practical vision tasks. His interests include automated visual inspection, surveillance, vehicle guidance and crime detection. He has published more than 200 papers, and three books - Machine Vision: Theory, Algorithms, Practicalities (1990), Electronics, Noise and Signal Recovery (1993), and Image Processing for the Food Industry (2000); the first of these has been widely used internationally for more than 20 years, and is now out in this much enhanced fourth edition. Roy holds a DSc at the University of London, and has been awarded Distinguished Fellow of the British Machine Vision Association, and Fellow of the International Association of Pattern Recognition.

    Readership

    Embedded, electronic systems, signal/image processing and computer engineering R&D engineers; post graduates and PhD researchers in machine and computer vision.

    E. R. Davies

    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.

    Affiliations and Expertise

    Royal Holloway, University of London, U.K.

    Computer and Machine Vision, 4th Edition

    1 Vision, the Challenge
    2 Images and Imaging Operations
    3 Basic Image Filtering Operations
    4 Thresholding Techniques
    5 Edge Detection
    6 Corner and Interest Point Detection
    7 Mathematical Morphology
    8 Texture
    9 Binary Shape Analysis
    10 Boundary Pattern Analysis
    11 Line Detection
    12 Circle and Ellipse Detection
    13 The Hough Transform and Its Nature
    14 Abstract Pattern Matching Techniques
    15 The Three-Dimensional World
    16 Tackling the perspective n-point problem
    17 Invariants and perspective
    18 Image transformations and camera calibration
    19 Motion
    20 Automated Visual Inspection
    21 Inspection of Cereal Grains
    22 Surveillance
    23 In-Vehicle Vision Systems24 Statistical Pattern Recognition
    25 Image Acquisition
    26 Real-Time Hardware and Systems Design Considerations
    27 Epilogue-Perspectives in Vision
    Appendix Robust statistics
    References
    Author Index
    Subject Index

     
     

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