Application of fuzzy quantifiers in image processing: a case study

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 (R.R. Yager's (1988) OWA approach), with respect to its suitability to model NL quantification over fuzzy image regions.