Expertise in classifying fingerprint patterns

Thompson and Tangen (2014) found that expert fingerprint examiners achieved a high level of accuracy in distinguishing prints from the same finger from prints from different fingers even when visual noise was added to the prints obscuring the ridge detail. We are interested in how well examiners can perform under similar “noisy” conditions compared to novices, but when asked to classify fingerprint patterns instead of performing a discrimination task. We know from other experiments we’ve conducted that expert examiners outperform novices in speed and accuracy when detecting, say, an odd loop in array of whorls, so we know that experts’ pattern classification performance already surpasses novices (e.g., Searston & Tangen, 2017). The question now is the extent to which this performance advantage persists when presented with prints that have been superimposed with a high degree of visual noise.