ARTISAN: a shape retrieval system based on boundary family indexing

Successful retrieval of images by shape feature is likely to be achieved only if we can mirror human similarity judgments. Following Biederman's theory of recognition-by-components, we postulate that shape analysis for retrieval should characterize an image by identifying properties such as collinearity, shape similarity and proximity in component boundaries. Such properties can then be used to group image components into families, from which indexing features can be derived. We are currently applying these principles in the development of the ARTISAN shape retrieval system for the UK Patent Office. The trademark images, supplied in compressed bit-map format, are processed using standard edge-extraction techniques to derive a set of region boundaries, which are approximated as a sequence of straight-line and circular-arc segments. These are then grouped into families using criteria such as proximity and shape similarity. Shape features for retrieval are then extracted from the image as a whole, each boundary family, and each individual boundary. Progress to date with the project is analyzed, evaluation plans described, and possible future directions for the research discussed.