Utilizing AFIS searching tools to reduce errors in fingerprint casework

Fifty-six (56) adjudicated, property crime cases involving fingerprint evidence were reviewed using a case-specific AFIS database tool. This tool allowed fingerprint experts to search latent prints in the cases against a database of friction ridge exemplars limited to only the individuals specific to that particular case. We utilized three different methods to encode and search the latent prints: automatic feature extraction, manual encoding performed by a student intern, and manual encoding performed by a fingerprint expert. Performance in the study was strongest when the encoding was conducted by the fingerprint expert. The results of the study showed that while the AFIS tools failed to locate all of the identifications originally reported by the initial fingerprint expert that worked the case, the AFIS tools helped to identify 7 additional latent prints that were not reported by the initial fingerprint expert. We conclude that this technology, when combined with fingerprint expertise, will reduce the number of instances where an erroneous exclusion could occur, increase the efficiency of a fingerprint unit, and be a useful tool for reviewing active or cold cases for missed opportunities to report identifications.