Beyond Minutiae: Inferring Missing Details from Global Structure in Fingerprints

Visual inference involves using prior knowledge and contextual cues to make educated guesses about incomplete or ambiguous information. This study explores visual inference as a function of expertise in the context of fingerprint examination, where professional examiners often need to piece together incomplete or partial visual evidence to identify individuals. 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). Consistent with our predictions, findings indicate that while both groups 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 of a print, enabling experts to make more accurate inferences about missing details. These results align with prior research on perceptual expertise in other domains, such as radiology and face recognition, and extend our understanding of scene-based categorisation to naturalistic object categorisation. Our research highlights the importance of experience and extensive exposure to a wide variety of prints in developing the perceptual skills needed for expert performance. These findings have implications for real-world tasks involving decisions based on limited or impoverished visual information, emphasizing the critical role of experience in detecting global summaries for accurate visual inferences.