Bayesian Approach to Image Interpretation
Springer Science & Business Media, Jul 31, 2001 - Computers - 127 pages
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:
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MRF FRAMEWORK FOR IMAGE INTERPRETATION 35
BAYESIAN NET APPROACH TO INTERPRETATION
JOINT SEGMENTATION AND IMAGE INTERPRETATION
Simulated Annealing AlgorithmSelecting T0 in
Appendix F kmeans clustering
Description ofAreaand Convex Area
Appendix H Knowledge Acquisition 107
1node Basis function
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