Fuzzy Sets for Modelling Fineness Perception in Texture Images

Abstract — Fineness is a primary texture feature frequently used for image content description. However, it is an ambiguous concept difficult to be characterized. To face this ambiguity, we propose to model the fineness by means of fuzzy sets, relating a representative fineness measure (our reference set) with the human perception of fineness. In our study, a wide variety of measures have been analyzed, defining a fuzzy set for each measure. The fineness perception has been collected from polls filled by human subjects, performing an aggregation of their assessments by means of OWA operators. For a given measure, the corresponding membership function is obtained by fitting the collected data. The performance of each fuzzy set is analyzed and checked with the human assessments, proposing a subgroup of them as the most adequate for modelling fineness perception in texture images

Use of aggregation functions in decision making

A key component of many decision making processes is the aggregation step, whereby a set of numbers is summarised with a single representative value. This research showed that aggregation functions can provide a mathematical formalism to deal with issues like vagueness and uncertainty, which arise naturally in various decision contexts