DOAJ Open Access 2022

Statistical feature training improves fingerprint-matching accuracy in novices and professional fingerprint examiners

Bethany Growns Alice Towler James D. Dunn Jessica M. Salerno N. J. Schweitzer +1 lainnya

Abstrak

Abstract Forensic science practitioners compare visual evidence samples (e.g. fingerprints) and decide if they originate from the same person or different people (i.e. fingerprint ‘matching’). These tasks are perceptually and cognitively complex—even practising professionals can make errors—and what limited research exists suggests that existing professional training is ineffective. This paper presents three experiments that demonstrate the benefit of perceptual training derived from mathematical theories that suggest statistically rare features have diagnostic utility in visual comparison tasks. Across three studies (N = 551), we demonstrate that a brief module training participants to focus on statistically rare fingerprint features improves fingerprint-matching performance in both novices and experienced fingerprint examiners. These results have applied importance for improving the professional performance of practising fingerprint examiners, and even other domains where this technique may also be helpful (e.g. radiology or banknote security).

Topik & Kata Kunci

Penulis (6)

B

Bethany Growns

A

Alice Towler

J

James D. Dunn

J

Jessica M. Salerno

N

N. J. Schweitzer

I

Itiel E. Dror

Format Sitasi

Growns, B., Towler, A., Dunn, J.D., Salerno, J.M., Schweitzer, N.J., Dror, I.E. (2022). Statistical feature training improves fingerprint-matching accuracy in novices and professional fingerprint examiners. https://doi.org/10.1186/s41235-022-00413-6

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Informasi Jurnal
Tahun Terbit
2022
Sumber Database
DOAJ
DOI
10.1186/s41235-022-00413-6
Akses
Open Access ✓