Computer scientists have answered a question that has nagged law enforcement and forensics experts for decades: Do fingerprint patterns change over time?
“We have now determined, with multilevel statistical modeling, that fingerprint recognition accuracy remains stable over time,” says Anil Jain, a professor of computer science and engineering at Michigan State University.
Jain, along with his former PhD student Soweon Yoon, who is now with the National Institute of Standards and Technology, used fingerprint records of 15,597 subjects apprehended multiple times by the Michigan State Police over a time span varying from five to 12 years.
The results show that fingerprint recognition accuracy doesn’t change even as the time between two fingerprints being compared increases.
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The paper by Yoon and Jain, published in the Proceedings of the National Academy of Sciences, is the largest and most thorough study of the persistence of Automated Fingerprint Identification Systems, or AFIS, accuracy.
Experts agree that Jain’s research addresses one of the most fundamental issues in fingerprint identification and is of great importance to law enforcement and forensic science.
“This study is one of the fundamental pieces of research on a topic that has always been taken for granted,” says Professor Christophe Champod of the Université de Lausanne in Switzerland. “Although operational practice has shown that the papillary patterns on our hands and feet are extremely stable and subject to limited changes (apart from scars), the study presented in PNAS provides empirical and statistical evidence.”
The National Science Foundation Center for Identification Technology Research supported the project.
Source: Michigan State University
