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Bayesian Approach to Image Interpretation 2001 Edition
Contributor(s): Kopparapu, Sunil K. (Author), Desai, Uday B. (Author)
ISBN: 0792373723     ISBN-13: 9780792373728
Publisher: Springer
OUR PRICE:   $161.49  
Product Type: Hardcover - Other Formats
Published: July 2001
Qty:
Annotation: Bayesian Approach to Image Interpretation will interest anyone working in image interpretation. It is complete in itself and includes background material. This makes it useful for a novice as well as for an expert. It reviews some of the existing probabilistic methods for image interpretation and presents some new results. Additionally, there is extensive bibliography covering references in varied areas. 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. Useful in both the academic and industrial research worlds, Bayesian Approach to Image Interpretation may also be used as a textbook for a semester course in computer vision or pattern recognition.
Additional Information
BISAC Categories:
- Technology & Engineering | Imaging Systems
- Mathematics | Probability & Statistics - General
- Computers | Computer Graphics
Dewey: 621.367
LCCN: 2001029596
Series: The Springer International Engineering and Computer Science
Physical Information: 0.38" H x 6.14" W x 9.21" (0.85 lbs) 127 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
Bayesian Approach to Image Interpretation will interest anyone working in image interpretation. It is complete in itself and includes background material. This makes it useful for a novice as well as for an expert. It reviews some of the existing probabilistic methods for image interpretation and presents some new results. Additionally, there is extensive bibliography covering references in varied areas.
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.
Useful in both the academic and industrial research worlds, Bayesian Approach to Image Interpretation may also be used as a textbook for a semester course in computer vision or pattern recognition.