: Structural queries constitute a special form of content-basedretrieval where the user specifiesa set of spatial constraints among query variables and asks for all configurations of actual objectsthat (totally or partially) match theseconstraints.Processingsuchqueriescanbethought of asa general form of spatial joins, i.e., instead of pairs, the result consistsof n-tuples of objects,where n is the numberof query variables.In this paperwe describea flexible frameworkwhich permits the representation of configurations in different resolution levels and supports the automatic derivation of similarity measures.We subsequentlyproposethree algorithms for structural query processing which integrate constraint satisfactionwith spatial indexing (R-trees).For eachalgorithm we apply several optimization techniques and experimentally evaluateperformanceusing realdata.