Robotics Book: Machine Vision, Third Edition: Theory, Algorithms, Practicalities (Signal Processing and its Applications)

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Book title: Machine Vision, Third Edition: Theory, Algorithms, Practicalities (Signal Processing and its Applications)

Machine Vision, Third Edition: Theory, Algorithms, Practicalities (Signal Processing and its Applications) Technical details/features and description:

In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications including surveillance, automated inspection, robot assembly, vehicle guidance, traffic monitoring and control, signature verification, biometric measurement, and analysis of remotely sensed images. While researchers and industry specialists continue to document their work in this area, it has become increasingly difficult for professionals and graduate students to understand the essential

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3 thoughts on “Robotics Book: Machine Vision, Third Edition: Theory, Algorithms, Practicalities (Signal Processing and its Applications)

  1. 15 of 15 people found the following review helpful:
    4.0 out of 5 stars
    Good survey of specific machine vision techniques, June 16, 2006
    By 
    calvinnme
    (VINE VOICE)
      
    (TOP 50 REVIEWER)
      

    This review is from: Machine Vision, Third Edition: Theory, Algorithms, Practicalities (Signal Processing and its Applications) (Hardcover)

    To begin with, the latest edition of this book was published in 2004, so all reviews dated earlier than that are referring to a previous edition. This book is a good one on issues and algorithms as they pertain to machine vision versus general computer vision. If you want a good general textbook on computer vision try “Computer Vision” by Linda Shapiro. It has all of the background material and a firm foundation in all of the topics you would expect in a course on computer vision. This book also has a section on introductory computer vision topics, I just don’t think it is as clear and as comprehensive as Shapiro’s book, especially for students.

    However, if you want an excellent treatment of the kinds of problems specific to machine vision – the detection of lines, holes, corners, circles, elipses, and polygons, for example, along with specific algorithm details, this book is very good. It also has good sections on pattern matching, motion estimation, and 3D machine vision. I would recommend it especially for those individuals who are already familiar with the basics of computer vision and would like a book on algorithms for solving specific problems in machine vision. I notice that Amazon only shows the table of contents for the previous edition, so I show the table of contents for the new edition next:

    1. Vision, The Challenge

    PART 1 – LOW-LEVEL VISION
    2. Images and Imaging Operations
    3. Basic Image Filtering Operations
    4. Thresholding Techniques
    5. Edge Detection
    6. Binary Shape Analysis
    7. Boundary Pattern Analysis
    8. Mathematical Morphology

    PART 2 – INTERMEDIATE-LEVEL VISION
    9. Line Detection
    10. Circle Detection
    11. The Hough Transform and Its Nature
    12. Ellipse Detection
    13. Hole Detection
    14. Polygon and Corner Detection
    15. Abstract Pattern Matching Techniques

    PART 3 – 3D VISION AND MOTION
    16. The Three-Dimensional World
    17. Tackling the Perspective n-Point Problem
    18. Motion
    19. Invariants and their Applications
    20. Egomotion and Related Tasks
    21. Image Transformations and Camera Calibration

    Part 4 – TOWARDS REAL-TIME PATTERN RECOGNITION SYSTEMS
    22. Automated Visual Inspection
    23. Inspection of Cereal Grains
    24. Statistical Pattern Recognition
    25. Biologically Inspired Recognition Schemes
    26. Texture
    27. Image Acquisition
    28. Real-Time Hardware and Systems Design Considerations

    PART 5 – PERSPECTIVES ON VISION
    29. Machine Vision, Art or Science?

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  2. 6 of 6 people found the following review helpful:
    5.0 out of 5 stars
    Solid Foundation to computer Vision, February 19, 2002
    By 
    Gamal Seedahmed (Richland, WA United States) –

    First of all I like this book very much. This book provides a solid and concrete foundation to computer vision from engineering point of view. The basic issues are treated very well in the conceptual and practical levels (e.g. edge detection). I came from a photogrammetry background, which means that the geometric aspects are very dominant in my thinking, and this book emphasize many geometric concepts in computer vision specially the treatment of Hough Transform as a main theme in the book. I recommend this book to the practitioners in spatial sciences (GIS, Remote sensing, Photogrammetry, etc) as well as the general community of computer vision.

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  3. 5 of 5 people found the following review helpful:
    5.0 out of 5 stars
    Excellent resource, August 3, 2001
    By 
    Peter Jensen (Ann Arbor, Mi United States) –

    Covers many aspects of vision, from basic image processing through high level scene analysis. It doesn’t always go down to the nitty-gritty source code level for every topic, but it does provide the direction to handle most every common machine vision problem. Of the ten or so general machine vision books on my easy-access shelf, this is the one I seem to pull down the most.

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