A Framework for Efficient Fingerprint Identification Using a Minutiae Tree

Given the existence of large fingerprint databases, including distributed systems, the development of algorithms for performing fast searches in them has become the important topic for biometric researchers. In this paper, we propose a new indexing method for fingerprint templates consisting of a set of minutia points. In contrast to previously presented methods, our algorithm is tree-based and well addresses the efficiency needs of complex (possibly distributed) systems. One large index tree is constructed and the enrolled templates are represented by the leaves of the tree. The branches in the index tree correspond to different local configurations of minutia points. Searching the index tree entails extracting local minutia neighborhoods of the test fingerprint and matching them against tree nodes. Therefore, the search time does not depend on the number of enrolled fingerprint templates, but only on the index tree configuration. This framework can be adapted for different tree-building parameters (feature sets, indexing levels, bin boundaries) according to user requirements and different enrollment and searching techniques can be applied to improve accuracy. We conduct a number of the experiments on Fingerprint Verification Competition databases, as well as the databases of synthetically generated fingerprint templates. The experiments confirm the ability of the proposed algorithm to find correct matches in the database and the minimum search time requirements.