Bayesian Approach to Image Interpretation

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.
   
  





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1. Ebooks list page : 605
2. Bayesian Approach to Image Interpretation
3. Desai, "Bayesian Approach to Image Interpretation"
4. Bayesian Core: A Practical Approach to Computational Bayesian Statistics (Springer Texts in Statisti
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