Digital Image Analysis

Selected Techniques and Applications

  • Walter G. Kropatsch
  • Horst Bischof

Table of contents

  1. Front Matter
    Pages i-xxx
  2. Mathematical Methods for Image Analysis

    1. Front Matter
      Pages 1-1
    2. Hans G. Feichtinger, Thomas Strohmer
      Pages 7-47
    3. Christian Cenker, Georg Pflug, Manfred Mayer
      Pages 49-79
    4. Josef Scharinger
      Pages 81-114
    5. Back Matter
      Pages 115-130
  3. Data Handling

    1. Front Matter
      Pages 131-131
    2. Pages 133-133
    3. Alois Goller, Ian Glendinning, Dieter Bachmann, Rainer Kalliany
      Pages 135-153
    4. Franz Niederl, Rainer Kalliany, Caterina Saraceno, Walter G. Kropatsch
      Pages 155-169
    5. Back Matter
      Pages 171-174
  4. Robust and Adaptive Image Understanding

    1. Front Matter
      Pages 175-175
    2. Pages 177-178
    3. Walter G. Kropatsch, Mark Burge, Roland Glantz
      Pages 179-197
    4. Walter G. Kropatsch, Horst Bischof, Roman Englert
      Pages 199-218
    5. Aleš Leonardis, Horst Bischof
      Pages 219-235
    6. Mark Burge, Wilhelm Burger
      Pages 237-249
    7. Edward Blurock
      Pages 251-263
    8. Back Matter
      Pages 265-280

About this book

Introduction

The human visual system as a functional unit including the eyes, the nervous system, and the corresponding parts of the brain certainly ranks among the most important means of human information processing. The e?ciency of the biological systems is beyond the capabilities of today’s technical systems, even with the fastest available computer systems. However, there are areas of application where digital image analysis systems produce acceptable results. Systems in these areas solve very specialized tasks, they operate in a limited environment, and high speed is often not necessary. Several factors determine the economical application of technical vision systems: cost, speed, ?exibility, robu- ness, functionality, and integration with other system components. Many of the recent developments in digital image processing and pattern recognition show some of the required achievements. Computer vision enhances the capabilities of computer systems • in autonomously collecting large amounts of data, • in extracting relevant information, • in perceiving its environment, and • in automatic or semiautomatic operation in this environment. The development of computer systems in general shows a steadily increasing need in computational power, which comes with decreasing hardware costs.

Keywords

3D Augmented Reality Digital Imaging calibration image analysis image compression image processing image understanding imaging object recognition pattern recognition remote sensing

Editors and affiliations

  • Walter G. Kropatsch
    • 1
  • Horst Bischof
    • 1
  1. 1.Pattern Recognition and Image Processing Group, Institute of Computer Aided AutomationVienna University of TechnologyViennaAustria

Bibliographic information

  • DOI https://doi.org/10.1007/b97375
  • Copyright Information Springer-Verlag New York, Inc. 2001
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-95066-2
  • Online ISBN 978-0-387-21643-0
  • About this book