Ultra fast fingerprint indexing for embedded system

A novel fingerprint indexing scheme for embedded system is presented in this paper. Our approach is a model-based one, which efficiently retrieves correct hypotheses using novel rotation-invariant features formed by the core and minutiae of fingerprint image. Differently from most existing fingerprint indexing approaches, the proposed algorithm is suitable for embedded systems because it is not time consuming and does not acquire large memory. Experiments were conducted on the FVC2002 database and our private database respectively. Experiment results based on FVC2002 database show that the time consuming for identification using proposed algorithm is about 50 times faster than the conventional approaches.