A framework for fuzzy recognition technology

We present a scheme for object recognition by classificatory problem solvin g in the framework of fuzzy sets and possibility theory. The scheme has a p articular focus on handling of the imperfection problems that are common in application domains where the objects to be recognized (detected and ident ified) represent undesirable situations, referred to as crises. Crises deve lop over time and observations typically increases in number and precision as the crisis develops, Early detection and precise recognition of crises i s desired, since it increases the possibility of an effective treatment. Th e crisis recognition problem is central in several areas of decision suppor t, such as in medical diagnosis, financial decisionmaking, and early warnin g systems. The problem is characterized by vague knowledge and observations suffering from several kinds of imperfections, such as missing information , imprecision, uncertainty, unreliability of the source, and mutual, possib le conflicting or reinforcing observations of the same phenomena, The probl em of handling possibly imperfect observations from multiple sources includ es the problems of information fusion and multiple sensor data fusion, The different kinds of imperfection are handled in the framework of fuzzy sets and possibility theory.