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Concise Computer Vision

An Introduction into Theory and Algorithms

  • Textbook
  • © 2014

Overview

Authors:
  1. Reinhard Klette

    1. Computer Science Department, University of Auckland, Auckland, New Zealand

    View author publications

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  • Presents an accessible general introduction to the essential topics in computer vision
  • Provides classroom-tested programming exercises and review questions at the end of each chapter
  • Includes supporting information on historical context, suggestions for further reading and hints on mathematical subjects under discussion
  • Includes supplementary material: sn.pub/extras

Part of the book series: Undergraduate Topics in Computer Science (UTICS)

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Table of contents (10 chapters)

  1. Front Matter

    Pages I-XVIII
    Download chapter PDF

  2. Image Data

    • Reinhard Klette
    Pages 1-42

  3. Image Processing

    • Reinhard Klette
    Pages 43-87

  4. Image Analysis

    • Reinhard Klette
    Pages 89-133

  5. Dense Motion Analysis

    • Reinhard Klette
    Pages 135-166

  6. Image Segmentation

    • Reinhard Klette
    Pages 167-214

  7. Cameras, Coordinates, and Calibration

    • Reinhard Klette
    Pages 215-243

  8. 3D Shape Reconstruction

    • Reinhard Klette
    Pages 245-286

  9. Stereo Matching

    • Reinhard Klette
    Pages 287-330

  10. Feature Detection and Tracking

    • Reinhard Klette
    Pages 331-374

  11. Object Detection

    • Reinhard Klette
    Pages 375-413

  12. Back Matter

    Pages 415-429
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Keywords

About this book

This textbook provides an accessible general introduction to the essential topics in computer vision. Classroom-tested programming exercises and review questions are also supplied at the end of each chapter. Features: provides an introduction to the basic notation and mathematical concepts for describing an image and the key concepts for mapping an image into an image; explains the topologic and geometric basics for analysing image regions and distributions of image values and discusses identifying patterns in an image; introduces optic flow for representing dense motion and various topics in sparse motion analysis; describes special approaches for image binarization and segmentation of still images or video frames; examines the basic components of a computer vision system; reviews different techniques for vision-based 3D shape reconstruction; includes a discussion of stereo matchers and the phase-congruency model for image features; presents an introduction into classification and learning.

Authors and Affiliations

  • Computer Science Department, University of Auckland, Auckland, New Zealand

    Reinhard Klette

About the author

Dr. Reinhard Klette, FRSNZ, is a Professor at the Tamaki Innovation Campus of The University of Auckland, New Zealand. His numerous other publications include the Springer title Euclidean Shortest Paths: Exact or Approximate Algorithms.

Bibliographic Information

  • Book Title: Concise Computer Vision

  • Book Subtitle: An Introduction into Theory and Algorithms

  • Authors: Reinhard Klette

  • Series Title: Undergraduate Topics in Computer Science

  • DOI: https://doi.org/10.1007/978-1-4471-6320-6

  • Publisher: Springer London

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer-Verlag London Ltd., part of Springer Nature 2014

  • Softcover ISBN: 978-1-4471-6319-0Published: 20 January 2014

  • eBook ISBN: 978-1-4471-6320-6Published: 04 January 2014

  • Series ISSN: 1863-7310

  • Series E-ISSN: 2197-1781

  • Edition Number: 1

  • Number of Pages: XVIII, 429

  • Number of Illustrations: 69 b/w illustrations, 229 illustrations in colour

  • Topics: Image Processing and Computer Vision, Artificial Intelligence

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