The Internet promises a worldwide information system, capable of uniting different sources and types of original, up-to-date and directly usable information. Among the main components of this system are retrieval mechanisms characterized by high precision and recall, as well as by supportive relevance feedback. The textual versions of these retrieval mechanisms have been available for some time and have achieved a certain degree of efficiency and sophistication. Image retrieval lags behind, despite the recent advances in content-based retrieval. In architecture this is largely due to the lack of integration of domain knowledge and known formalisms. Indexing and retrieval of architectural floor plans can rely on existing generative systems such as shape grammars and rectangular arrangements. By reversing generative systems in purpose we derive compact descriptions that describe completely a floor plan and make explicit all relevant features rather than a small number of features. The main limitation of reversed generative systems is that they apply to specific classes of designs. Unification in indexing and retrieval can only take place at the level of basic primitives, i.e. spaces and building elements. In both vector and pixel images of architectural floor plans this can be achieved by a universal recognition system that identifies salient local features to produce a basic spatial representation.
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