Optimal Fuzzy Aggregation of Secondary Attributes in Recognition Problems

Abstract

A method of optimal fuzzy aggregation of secondary attributes in problems of recognizing a person from images is proposed. The primary attribute is a characteristic feature of an object, allowing to distinguish one object from another. The secondary attribute is a result of recognition algorithm, based on primary attributes. Fuzzy integrals of Sugeno and Choquet are used as aggregation operators of secondary attributes. Optimality of aggregation here stands for the selection of the best solution of recognition problem by means of fuzzy integrals. It also indicates conditions, when the use of Sugeno fuzzy integral as an aggregation operator is better than the use of Choquet fuzzy integral in recognition problems. The experiment results are presented.