Bayesian Approach to Image Interpretation

Bayesian Approach to Image Interpretation (The Kluwer International Series in Engineering and Computer Science, Volume 616) (The International Series in Engineering and Computer Science) bySunil K. Kopparapu (Author), Uday B. Desai (Author)

Publisher: Springer; 1 edition (July 1, 2001) | ISBN-10: 0792373723 | DjVu | 1,4 Mb | 144 pages

Bayesian Approach to Image Interpretation will interestanyone working in image interpretation. It is complete in itself andincludes background material. This makes it useful for a novice aswell as for an expert. It reviews some of the existing probabilisticmethods for image interpretation and presents some new results.Additionally, there is extensive bibliography covering references invaried areas.For a researcher in this field, the material on synergisticintegration of segmentation and interpretation modules and theBayesian approach to image interpretation will be beneficial.For a practicing engineer, the procedure for generating knowledgebase, selecting initial temperature for the simulated annealingalgorithm, and some implementation issues will be valuable.New ideas introduced in the book include:Newapproach to image interpretation using synergism between thesegmentation and the interpretation modules.A new segmentationalgorithm based on multiresolution analysis.Novel use of theBayesian networks (causal networks) for image interpretation.Emphasis on making the interpretation approach less dependent on theknowledge base and hence more reliable by modeling the knowledge basein a probabilistic framework.Useful in both the academic and industrial research worlds,Bayesian Approach to Image Interpretation may also be usedas a textbook for a semester course in computer vision or patternrecognition.

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