A new non-contact, 3-D fingerprinting system could make spotting the bad guys faster and easier, whether it’s at the border or the police precinct. By projecting patterns of light onto a finger and analyzing the image, researchers from the University of Kentucky are able to create a more accurate print than those made with ink or sensor plates. The researchers say the system is more efficient than traditional fingerprinting and significantly reduces the number of incorrect matches.
“Fingerprinting has been widely applied to identify criminals in forensic law enforcement and security applications,” says Yongchang Wang, a PhD candidate at the University of Kentucky, and lead author of a paper on the fingerprinting research. But traditional techniques, Wang says, don’t make it easy to gather accurate, detailed prints.
Even the modern approach, in which the subject’s finger is rolled over a glass plate for scanning, often requires several attempts per finger to get a usable print. The glass also must be cleaned after each scan. And capturing prints of all 10 fingers can take several minutes.
“The customs agent has a budget of 32 seconds per person. They need a way to get your fingerprints quickly,” says Mike Troy, chief executive officer of FlashScan3D, a company based in Richardson, TX, that was founded to commercialize the Kentucky system.
The device works by projecting a series of striped lines onto a finger, in a process called structured light illumination (SLI). A 1.4 megapixel camera automatically captures images of the lines as they wrap around the finger, at roughly 1,000 pixels per inch. That’s twice as much as the resolution required for a fingerprint in the FBI’s Automatic Fingerprint Identification System (AFIS). By analyzing the way each line rises and falls, the software builds a 3-D model of the surface of the finger in less than a second, with each ridge and valley in its proper place. And unlike existing fingerprinting devices, the SLI system isn’t hampered by oily skin or a dry environment.
Existing scanning systems, which capture a print in two dimensions, require the pressing or rolling of a finger onto a rigid plane. Because the skin is elastic, the print is distorted, Wang says, adding that the SLI system has no such contact or distortion. “So, even at the same resolution, the non-contact 3-D print will have a much better performance in matching than traditional 2-D,” he says.
According to Daniel Lau, associate professor of electrical engineering at Kentucky and Wang’s supervisor on the project, on a scale of 1 to 5, with 1 representing the highest quality image possible and 5 representing unusable quality, their SLI system scored 1.1519. In contrast, a popular commercial 2-D fingerprint scanner scored 1.7125. The difference is both statistically and practically significant, Lau says. “It translates into an improvement in matching performance.” Plans to significantly expand the FBI’s biometric database mean that it is even more important to make fast, accurate matches, he says.
Shahram Orandi, team leader for the National Institute of Standards and Technology’s large-scale biometrics systems testing group, says 3-D fingerprinting is a hot area of development. Both the Department of Homeland Security and the National Institutes of Justice are interested in a non-contact system that can capture 3-D prints, ideally gathering data from multiple fingers at once. “There’s money out there and people are jumping at it,” Orandi says. Carnegie Mellon University and TBS Holdings are independently working on systems that use multiple cameras to capture the prints, for example. Both projects, as well as Kentucky’s, have received government grants.
“Almost everybody that tried to achieve 3-D capture has succeeded,” Orandi says. “The missing secret sauce is how to make these images compare to existing technology.”
Orandi describes the problem by equating a fingerprint to a tangerine peel. Trying to flatten out a carefully removed, large piece of peel will break the skin. The same thing happens with 3-D fingerprints, he says. Flattening them into 2-D images, so that they can be compared against the traditional prints in AFIS, results in cracks.
Wang says his system is able to flatten the 3-D representations it creates into two-dimensional prints without distorting the image. NIST is developing tools to test 3-D fingerprinting systems and assess the differences between some of the schemes being developed.
While he declined to go into detail on how Kentucky’s system fares against others, Orandi did say that it was among the top three he was familiar with.
The University of Kentucky researchers hope to improve their system, initially by speeding up the system so that the scanning and processing time is reduced to less than 0.1 seconds. The team also wants to be able to scan all 10 fingers at once, too. “Our goal is to have a box with multiple scanners in it … where you can just hold a relaxed hand pose” and capture the prints on all 10 fingers, says Lau.
This new data poisoning tool lets artists fight back against generative AI
The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models.
Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist
An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work.
The Biggest Questions: What is death?
New neuroscience is challenging our understanding of the dying process—bringing opportunities for the living.
Driving companywide efficiencies with AI
Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.