Management of Uncertainty in Top-Down, fuzzy Logic-Based Image Understanding of Natural Objects

This paper is concerned with the integration of knowledge intensive methods with low level image processing, in order to achieve a top-down image processing system. The knowledge part contains information about the object to be recognized, the model, expressed here as a part-of hierarchy, and expert knowledge on image processing. Both of these bodies of knowledge are allowed to be imprecise and/or incomplete, in which case fuzzy logic based methods are used for representation and inference. As a consequence, uncertainty management issues, such as partial matching, and evidence combination must be addressed. The approach proposed is most suitable for complex/natural objects and is illustrated for the task of recognizing a human face.