A study of the emotional evaluation models of color patterns based on the adaptive fuzzy system and the neural network

Proposed in this article are two kinds of emotional models based on the neural network and the adaptive fuzzy system that can transform the physical features of a color pattern into its emotional features. The purpose of this system of models is to evaluate the neural network and adaptive fuzzy system for its ability to model psychological experimental data in a way similar to what a human expert would do. Construction of the models was motivated by Soen's psychological experiments, in which he found that such physical features as average hue, saturation, and intensity and the dynamic components of color patterns affected the emotional features represented by a pair of adjectives having opposite meanings. One is based on the neural network in the proposed models, and the other consists of two adaptive fuzzy rule bases and a γ model, a fuzzy set operator, to fuse the evaluation values produced by them. The proposed models showed superior performances compared to Soen's model in the approximation of nonlinear transforms, whereas the latter showed an advantage in obtaining the linguistic interpretation from the trained results. The evaluated results of color patterns can be used to construct a emotion‐based color‐pattern retrieval system, which would be able to recommend the color patterns of a desired human feeling. We believe that in linguistic queries of human feelings, these color‐pattern retrieval systems would be able to select from a gallery the corresponding textile designs, wallpapers, or pictures. © 2002 Wiley Periodicals, Inc. Col Res Appl, 27, 208–216, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10052