Filtering large fingerprint database for latent matching

Latent fingerprint identification is of critical importance to law enforcement agencies in apprehending criminals. Considering the huge size of fingerprint databases maintained by law enforcement agencies, exhaustive one-to-one matching is impractical and a database filtering technique is necessary to reduce the search space. Due to low image quality and small finger area of latent fingerprints, it is necessary to use several features for an efficient and reliable filtering system. A multi-stage filtering system is proposed, which utilizes pattern type, singular points and orientation field. We have tested our system by searching 258 latent fingerprints in NIST SD27 against a background database containing 10,258 rolled fingerprints (obtained by combining 2,000 in NIST SD4, 8,000 in SD14 and 258 in SD27). Although latent fingerprints contain very limited information, the filtering system not only improved the matching speed by three fold but also improved the rank-1 matching accuracy from 70.9% to 73.3%.