'First 3D fingerprint model' to help improve print-matching technology

 
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'First 3D fingerprint model' to help improve print-matching technology
A team of Michigan State University computer scientists led by Indian Institute of Technology (IIT) Kanpur alum Anil Jain 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, according to information posted on MSU website.

What Jain, a University Distinguished Professor of computer science and engineering, and his team did was develop a method that takes a two-dimensional image of a fingerprint and maps it to a 3D finger surface.

The 3D finger surface, complete with all the ridges and valleys that make up the human fingerprint, is made using a 3D 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 3D 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."

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 3D fingerprint phantom, I know its precise measurements," said Jain. "And because I know the true dimensions of the fingerprint features on this phantom, I can better evaluate fingerprint readers."

While the 3D 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.

Members of Jain's team include Sunpreet Arora, a computer science doctoral student, Kai Cao, a research associate in computer science and engineering and research collaborator Nick Paulter at the National Institute of Standards and Technology

Jain, who has a B.Tech degree from IIT Kanpur and MS and PhD degrees from Ohio State University, has six US patents on fingerprint matching and has written a number of books on biometrics and fingerprint/facial recognition.

Additionally, Jain has also received a number of prestigious awards for contributions to pattern recognition and biometrics.

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