Beyond minutiae: inferring missing details from global structure in fingerprints.

Abstract

Visual inference involves using prior knowledge and contextual cues to make educated guesses about incomplete or ambiguous information. This study explores the role of visual inference as a function of expertise in the context of fingerprint examination, where professional examiners need to determine whether two fingerprints were left by the same person, or not, often based on limited or impoverished visual information. We compare expert and novice performance on two tasks: inferring the missing details of a print at an artificial blank spot (Experiment 1) and identifying the missing surrounds of a print given only a small fragment of visual detail (Experiment 2). We hypothesized that experts would demonstrate superior performance by leveraging their extensive experience with global fingerprint patterns. Consistent with our predictions, we found that while both experts and novices performed above chance, experts consistently outperformed novices. These findings suggest that expertise in fingerprint examination involves a heightened sensitivity to gist, or global image properties within a print, enabling experts to make more accurate inferences about missing details. These results align with prior research on perceptual expertise in other expert domains, such as radiology, and extend our understanding of scene and face recognition to fingerprint examination. Our findings show that expertise emerges from an ability to combine local and global visual information-experts skillfully process both the fine details and overall patterns in fingerprints. This research provides insight into how perceptual expertise supports accurate visual discrimination in a high-stakes, real-world task with broader implications for theoretical models of visual cognition.