The use of psychological similarity measure for queries in image databases

With complex multimedia data, we see the emergence of database systems in which the fundamental operation is similarity assessment. Before database issues can be addressed, it is necessary to give a definition of similarity as an operation. In this paper we study several models proposed in the psychological literature to explain the characteristics of human similarity assessment, and discuss their computational characteristics. In addition, we develop a similarity measure, based on fuzzy logic, that exhibit several features that match experimental findings in humans. The model is dubbed Fuzzy Feature Contrast (FFC) and is an extension to a more general domain of the Feature Contrast model due to Tversky. We show how the FFC model can be used to model similarity assessment from fuzzy judgment of properties, and we address the use of fuzzy measures to deal with dependencies among the properties. Finally, we show how the parameters of the model can be tuned by comparative judgment experiments.