Automated fingerprint recognition has received considerable attention over the past decade. Progress has been made on models of the structure of fingerprints, techniques for the acquisition of prints, and the development of commercial automated fingerprint recognition systems. Despite these advances, there remain considerable opportunities for improvement. The speed of retrieval, and the ability to recognize partial or distorted prints are prominent among those areas that require improvement. This study will describe a structural model of fingerprints, based on local structural relations among features, and an associated automated recognition system which addresses the limitations of existing fingerprint models.