Color in Computer Vision: Fundamentals and Applications

Color in Computer Vision: Fundamentals and Applications

Author(s): Theo Gevers, Arjan Gijsenij, Joost van de Weijer, Jan-Mark Geusebroek

Published Online: 21 AUG 2012 08:28PM EST

Print ISBN: 9780470890844

Online ISBN: 9781118350089

DOI: 10.1002/9781118350089

About this Book

While the field of computer vision drives many of today's digital technologies and communication networks, the topic of color has emerged only recently in most computer vision applications. One of the most extensive works to date on color in computer vision, this book provides a complete set of tools for working with color in the field of image understanding.

Based on the authors' intense collaboration for more than a decade and drawing on the latest thinking in the field of computer science, the book integrates topics from color science and computer vision, clearly linking theories, techniques, machine learning, and applications. The fundamental basics, sample applications, and downloadable versions of the software and data sets are also included. Clear, thorough, and practical, Color inComputer Vision explains:

  • Computer vision, including color-driven algorithms and quantitative results of various state-of-the-art methods
  • Color science topics such as color systems, color reflection mechanisms, color invariance, and color constancy
  • Digital image processing, including edge detection, feature extraction, image segmentation, and image transformations
  • Signal processing techniques for the development of both image processing and machine learning
  • Robotics and artificial intelligence, including such topics as supervised learning and classifiers for object and scene categorization Researchers and professionals in computer science, computer vision, color science, electrical engineering, and signal processing will learn how to implement color in computer vision applications and gain insight into future developments in this dynamic and expanding field.

Table of contents

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  1. Part I: Color Fundamentals

  2. Part II: Photometric Invariance

    1. Chapter 6

      Derivative-Based Photometric Invariance (pages 81–112)

      With contributions by Rein van den Boomgaard and Arnold W. M. Smeulders

    2. Chapter 7

      Photometric Invariance by Machine Learning (pages 113–134)

      With contributions by José M. Álvarez and Antonio M. López

  3. Part III: Color Constancy

  4. Part IV: Color Feature Extraction

    1. Chapter 13

      Color Feature Detection (pages 187–220)

      With contributions by Arnold W. M. Smeulders and Andrew D. Bagdanov

    2. Chapter 14

      Color Feature Description (pages 221–243)

      With contributions by Gertjan J. Burghouts

    3. Chapter 15

      Color Image Segmentation (pages 244–268)

      With contributions by Gertjan J. Burghouts

  5. Part V: Applications

    1. Chapter 16

      Object and Scene Recognition (pages 269–286)

      With contributions by Koen E. A. van de Sande and Cees G. M. Snoek

    2. Chapter 17

      Color Naming (pages 287–317)

      With contributions by Robert Benavente, Maria Vanrell, Cordelia Schmid, Ramon Baldrich, Jakob Verbeek and Diane Larlus

    1. You have free access to this content
    1. You have free access to this content
    1. You have free access to this content