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Machine Vision

£51.99

textbook
  • Date Published: November 2010
  • availability: Available
  • format: Paperback
  • isbn: 9780521169813

£ 51.99
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  • This 2004 book is an accessible and comprehensive introduction to machine vision. It provides all the necessary theoretical tools and shows how they are applied in actual image processing and machine vision systems. A key feature is the inclusion of many programming exercises that give insights into the development of practical image processing algorithms. The authors begin with a review of mathematical principles and go on to discuss key issues in image processing such as the description and characterization of images, edge detection, restoration and feature extraction, segmentation, texture and shape. They also discuss image matching, statistical pattern recognition, clustering, and syntactic pattern recognition. Important applications are described, including optical character recognition and automatic target recognition. Software and data used in the book can be found at www.cambridge.org/9780521830461. A useful reference for practitioners, the book is aimed at graduate students in electrical engineering, computer science and mathematics.

    • Describes essential theoretical background as well as cutting-edge applications
    • Includes many programming exercises that give insight into the development of image processing algorithms
    • A CD-ROM containing software and data used in the book is provided
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    Product details

    • Date Published: November 2010
    • format: Paperback
    • isbn: 9780521169813
    • length: 452 pages
    • dimensions: 246 x 189 x 23 mm
    • weight: 0.8kg
    • availability: Available
  • Table of Contents

    1. Introduction
    2. Review of mathematical principles
    3. Writing programs to process images
    4. Images: description and characterization
    5. Linear operators and kernels
    6. Image relaxation: restoration and feature extraction
    7. Mathematical morphology
    8. Segmentation
    9. Shape
    10. Consistent labeling
    11. Parametric transform
    12. Graphs and graph-theoretic concepts
    13. Image matching
    14. Statistical pattern recognition
    15. Clustering
    16. Syntactic pattern recognition
    17. Applications
    18. Automatic target recognition.

  • Resources for

    Machine Vision

    Wesley E. Snyder, Hairong Qi

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    Please use locked resources responsibly and exercise your professional discretion when choosing how you share these materials with your students. Other lecturers may wish to use locked resources for assessment purposes and their usefulness is undermined when the source files (for example, solution manuals or test banks) are shared online or via social networks.

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    If you are having problems accessing these resources please contact lecturers@cambridge.org.

  • Authors

    Wesley E. Snyder, North Carolina State University

    Hairong Qi, University of Tennessee, Knoxville

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