Performance evaluation of a fuzzy fusion system for subsoil classification

An information fusion system is proposed in this paper in order to segment seismic images in geological regions. The fusion of the attributes considered is made according to image interpreter knowledge, coded in the fuzzy subset theory formalism. The focus is on the problem of a quantitative performance evaluation of the fusion system according to the interpreter qualitative assessment, which has been translated into three main properties. The Baddeley distance is a potential operator for such a performance evaluation and the interesting results obtained with it are presented. But further developments are needed to calibrate the Baddeley distance more precisely with interpreter behavior and thus to optimize the fuzzy fusion system in an automatic way.