Research on the local regional similarity of automatic fingerprint identification system fingerprints based on close non‐matches in a ten million people database—Taking the central region of whorl as an example

Abstract

The local regional similarity of fingerprints has always been a hot issue in the field of fingerprint research. With the increasing size of ten-print databases, the appearance of close non-matches (CNMs) in automatic fingerprint identification system (AFIS) candidate lists has attracted increasing attention from forensic science departments worldwide. In this study, three categories (high-, medium-, and low-level) of standards for CNMs were established and 60 whorl samples were marked with different numbers of minutiae to explore the occurrence and influencing factors of CNMs in AFIS candidate lists based on a ten million people database. The results showed that all prints could be found with their corresponding CNMs. The average occurrence rate of CNMs for every query was 52.7% in the top 100 lists, and the most similar CNM was exactly the same in the local area of 12 coincidence points. CNMs appeared more in the middle and lower parts of the central region of the whorl. Moreover, shorter C2C distances and the same finger number and hand led to more CNMs being inspected. CNMs with higher similarity required a more extensive regional area and smaller minutiae density. We concluded that CNMs have a high occurrence rate in large-scale databases and many factors are closely related to them. Fingerprint examiners and researchers need to strengthen their understanding of CNMs to avoid the occurrence of misidentification like the Madrid bombings.