Overview
- Editors:
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Walter G. Kropatsch
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Pattern Recognition and Image Processing Group, Institute of Computer Aided Automation, Vienna University of Technology, Vienna, Austria
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Horst Bischof
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Pattern Recognition and Image Processing Group, Institute of Computer Aided Automation, Vienna University of Technology, Vienna, Austria
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Table of contents (22 chapters)
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Mathematical Methods for Image Analysis
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- Hans G. Feichtinger, Thomas Strohmer
Pages 7-47
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- Christian Cenker, Georg Pflug, Manfred Mayer
Pages 49-79
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Back Matter
Pages 115-130
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Data Handling
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Front Matter
Pages 131-131
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- Alois Goller, Ian Glendinning, Dieter Bachmann, Rainer Kalliany
Pages 135-153
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- Franz Niederl, Rainer Kalliany, Caterina Saraceno, Walter G. Kropatsch
Pages 155-169
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Back Matter
Pages 171-174
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Robust and Adaptive Image Understanding
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Front Matter
Pages 175-175
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- Walter G. Kropatsch, Mark Burge, Roland Glantz
Pages 179-197
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- Walter G. Kropatsch, Horst Bischof, Roman Englert
Pages 199-218
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- Aleš Leonardis, Horst Bischof
Pages 219-235
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- Mark Burge, Wilhelm Burger
Pages 237-249
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Back Matter
Pages 265-280
About this book
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.
