A team of Michigan State University computer scientists have built the first three-dimensional model of a human fingerprint. This development is expected to help fingerprint-matching technology as well as create improvements in security.
The team was led by Anil Jain, Nick Paulter and MSU colleagues, including Sunpreet Arora and Kai Cao. The researchers developed a method that takes a 2D image of a fingerprint and maps the image to a 3D finger surface. The 3D finger surface is made with a 3D printer, which prints out all of the ridges and valleys of a fingerprint, what Jain’s team calls a fingerprint “phantom.”
Imaging phantoms are used in medical images, such as making sure an MRI machine or CT scanner is working. An image of known dimensions is used to ensure the machines are accurate.
“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.”
The goal is to have a precise fingerprint model with known properties and features to calibrate existing technology used for fingerprint-matching.
“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.”
“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.