Application of fuzzy quantifiers in image processing: A case study

Ingo Gloeckner, Alois Knoll

Research output: Contribution to conferencePaperpeer-review

4 Scopus citations

Abstract

Fuzzy quantifiers, i.e. operators intended to provide a numerical interpretation of natural language (NL) quantifiers like `almost all', are valuable tools for image processing, in particular to express accumulative (second order) properties of fuzzy image regions. However, approaches to fuzzy quantification will unfold their full potential only if the proposed operators capture the meaning of NL quantifiers. We present an exemplary evaluation of one of the most prominent approaches to fuzzy quantification, Yager's OWA approach, with respect to its suitability to model NL quantification over fuzzy image regions.

Original languageEnglish
Pages259-262
Number of pages4
StatePublished - 1999
Externally publishedYes
EventProceedings of the 1999 3rd International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES '99) - Adelaide, Aust
Duration: 31 Aug 19991 Sep 1999

Conference

ConferenceProceedings of the 1999 3rd International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES '99)
CityAdelaide, Aust
Period31/08/991/09/99

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