Overview
Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 616)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents(6 chapters)
About this book
For a researcher in this field, the material on synergistic integration of segmentation and interpretation modules and the Bayesian approach to image interpretation will be beneficial.
For a practicing engineer, the procedure for generating knowledge base, selecting initial temperature for the simulated annealing algorithm, and some implementation issues will be valuable.
New ideas introduced in the book include:
- New approach to image interpretation using synergism between the segmentation and the interpretation modules.
- A new segmentation algorithm based on multiresolution analysis.
- Novel use of the Bayesian networks (causal networks) for image interpretation.
- Emphasis on making the interpretation approach less dependent on the knowledge base and hence more reliable by modeling the knowledge base in a probabilistic framework.
Authors and Affiliations
-
Research and Development Group, Aquila Technologies Private Limited, Bangalore, India
Sunil K. Kopparapu
-
SPANN Lab. Department of Electrical Engineerin, Indian Institute of Technology -Bombay, Powai, Mumbai, India
Uday B. Desai
Bibliographic Information
Book Title: Bayesian Approach to Image Interpretation
Authors: Sunil K. Kopparapu, Uday B. Desai
Series Title: The Springer International Series in Engineering and Computer Science
DOI: https://doi.org/10.1007/b117231
Publisher: Springer New York, NY
-
eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 2000
Hardcover ISBN: 978-0-7923-7372-8Published: 31 July 2001
Softcover ISBN: 978-1-4757-7483-2Published: 23 March 2013
eBook ISBN: 978-0-306-46996-1Published: 25 November 2005
Series ISSN: 0893-3405
Edition Number: 1
Number of Pages: XV, 127
Topics: Image Processing and Computer Vision, Computer Imaging, Vision, Pattern Recognition and Graphics, Computer Graphics, Computer Communication Networks