Object recognition based on comparative similarity assessment

Abstract

In the paper a concept of object recognition based on their similarity assessment in case of nonhomogenous qualitative and quantitative objects’ features is presented. Moreover, it is assumed that the features’ intensity values are not given directly but by their pairwise comparative assessment. This corresponds to an intuitive, on human experience-based assessment of the objects’ properties. The proposed object recognition method is based on reference sets divided into credibility layers, according to a relative logical model and conceptual classes of similarity. This concept is illustrated by an example of a conceptual class of “irregular” objects, the “irregularity” being intuitively assessed. The method is presented in the form of an algorithm.