Information fusion in computer vision using the fuzzy integral

A method of evidence fusion, based on the fuzzy integral, is developed. This technique nonlinearly combines objective evidence, in the form of a fuzzy membership function, with subjective evaluation of the worth of the sources with respect to the decision. Various new theoretical properties of this technique are developed, and its applicability to information fusion in computer vision is demonstrated through simulation and with object recognition data from forward-looking infrared imagery.<>