The organization and the functional components of software environments that have been developed for image understanding (IU) are described. The basic components of general IU environments are detailed with respect to representations, programming constructs, system-specific databases and user interfaces. How these components have been realized in different systems through examples and possible developments in the near future are discussed.>

We present an architecture for terrain recognition for an autonomous land vehicle. Basic components of this are a set of data bases for generic object models, perceptual structures, temporary memory for the instantiation of object and relational hypothesis, and a long term memory for storing stable hypothesis which are affixed to the terrain representation. Different inference processes operate over these data bases. We describe components of this architecture: the perceptual structure data base, the grouping processes that operate over this, and schemas. We conclude with a processing example for matching predictions from the long term terrain model to imagery and extracting significant perceptual structures for consideration as potential landmarks.