Overview
Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 616)
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Table of contents (6 chapters)
Keywords
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
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
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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