Beyond the individuality of fingerprints: a measure of simulated computer latent print source attribution accuracy
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Efforts to harness computer fingerprint databases to perform studies relevant to fingerprint identification have tended to focus on 10-print, rather than latent print, identification or on the inherent individuality of fingerprint images. This paper reports on three experiments that measure the accuracy of a computer fingerprint matcher at identifying the source of simulated latent prints. The first experiment used rolled prints supplied by the National Institute of Standards and Technology (NIST) to simulate latent prints. The second experiment used our own manufactured latent prints. The third experiment used latent prints supplied by NIST. An Automated Fingerprint Identification System (AFIS) was used to simulate the task that a human latent print examiner is typically asked to perform as part of ordinary casework. The AFIS performed this task, for which it was not designed, fairly well. However, there are non-mate images that scored very highly on the AFIS's similarity measure. These images would be susceptible to erroneous conclusions that would be given with a very high degree of confidence. Not surprisingly, the same was also true of the simulated latents which contained less information. We suggest that measuring the accuracy and potential for erroneous conclusions for AFISs might provide a basis for comparison between human examiners and automated systems at performing various identification tasks. Such comparisons might stimulate competition, innovation and improvement in the performance of these tasks.
Law, Probability and Risk
Criminology not elsewhere classified