Expertise in classifying fingerprints by hands and fingers

Fingerprint classification decisions—Is this print from a left or right hand? Is it a thumb, index, middle, ring or little finger?—are central to the upstream fingerprint examination process. Computer algorithms are used to narrow down the search of large national fingerprint databases to a much smaller list of the most highly similar candidate prints. But it is not uncommon for this search process to return dozens of candidate prints for the human examiner to sift through. To help narrow this list even further, fingerprint examiners can nominate which type of finger they think left the latent print: a left or right little, ring, middle, index or thumb. A misclassification of a latent print could wrongly exclude genuine candidates from further examination. Accurate hand and finger classification, on the other hand, helps to exclude candidates that are not a match before the comparison stage, speeding up the process. This project focuses on hand and finger classification as just one particular aspect of the fingerprint examination process. As a first test of hand and finger classification decisions, fingerprint experts and novices are asked to classify prints as belonging to a left or right little, ring, middle, index or thumb. Our goal is to first establish if people can classify prints by hand and finger type above chance. We will then explore whether fingerprint classification performance is a distinguishing feature of visual expertise in fingerprints, setting experienced practitioners apart from novices.