LANSING (WWJ) — A team of computer scientists in the Michigan State University College of Engineering have built the first three-dimensional model of a human fingerprint.

This development will not only help today’s fingerprint-matching technology do its job better, but could eventually lead to improvements in security.

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What Anil Jain, his MSU colleagues and research collaborator Nick Paulter at the National Institute of Standards and Technology did was develop a method that takes a two-dimensional image of a fingerprint and maps it to a 3-D finger surface.

The 3-D finger surface, complete with all the ridges and valleys that make up the human fingerprint, is made using a 3-D printer. It creates what Jain’s team called a fingerprint “phantom.”

Imaging phantoms are common in the world of medical imaging. For example, to make sure an MRI machine or a CT scanner is working properly, it needs to first image an object of known dimensions and material properties.

“In health care, a 3-D heart or kidney can be created,” Jain said. “Because the dimensions are known, they can be put into a scanner and the imaging system can be calibrated.”

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In this case, the ultimate goal is to have a precise fingerprint model with known properties and features that can be used to calibrate existing technology used to match fingerprints.

“When I have this 3-D fingerprint phantom, I know its precise measurements,” said Jain, a University Distinguished Professor of computer science and engineering. “And because I know the true dimensions of the fingerprint features on this phantom, I can better evaluate fingerprint readers.”

While the 3-D model doesn’t yet have the exact texture or feel of a real finger, it could advance fingerprint sensing and matching technology.

“Tools like this would help improve the overall accuracy of fingerprint-matching systems, which eventually leads to better security in applications ranging from law enforcement to mobile phone unlock,” Jain said.

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Members of Jain’s team include Sunpreet Arora, a computer science doctoral student, and Kai Cao, a research associate in computer science and engineering.