Dealing with uncertainty and imprecision in image segmentation using belief function theory.
Benoît LelandaisIsabelle GardinLaurent MouchardPierre VeraSu RuanPublished in: Int. J. Approx. Reason. (2014)
Keyphrases
- belief functions
- imprecise probabilities
- image segmentation
- dempster shafer
- possibility theory
- probability theory
- uncertain information
- handling uncertainty
- dempster shafer theory
- fuzzy numbers
- multicriteria decision making
- uncertain reasoning
- probability function
- evidential reasoning
- expected utility
- fuzzy measures
- markov tree
- graph cuts
- fuzzy logic
- bayesian networks
- computer vision
- theoretical framework
- probabilistic graphical models
- information processing
- knowledge based systems
- utility theory
- pattern recognition
- data structure
- image processing