Core upgrades
In NGI, the ten-print system has also been improved because it now runs on a more powerful, 1,000-blade server farm -- the old IAFIS system runs on 64 blades -- and uses enhanced recognition algorithms. "NGI is faster, more accurate, and has better process flows than IAFIS had," says Blanchard.
The matching accuracy rate has risen from 92% to 99% while average response time has dropped from 2 hours to 10 minutes. "That changes the game at the local police station," says Art Ibers, director of the NGI program at government contractor Lockheed Martin.
But the time improvement is for matching fingerprints scanned under controlled conditions, such as at a police booking station. Matching latent fingerprints -- those found at a crime scene -- is much more difficult. With an accuracy rate of just 25%, IAFIS wasn't highly effective for investigators. By contrast, the upgraded NGI capabilities rolled out in May 2013 have had an accuracy rate well above 80% for latents, due to an improved algorithm that takes advantage of more compute horsepower, Reid says.
Going for the palm
A national palm-print database, deployed in May 2013, should also help investigators because palm prints are left at the crime scene 30% of the time. "There will be significant leads around cold cases that we couldn't have gotten before," Reid says.
The State of Michigan has been taking palm prints for five years, but Blanchard says there have been a few kinks getting up and running with the new system. "The FBI has placed requirements on palm print submissions that most states are not meeting," he says.
In a palm capture, NGI requires that the whole hand be captured, not just the palm. "They are trying to compare the fingers from the palm capture to the fingerprints that were rolled to make sure the palm matches the person. Many agencies aren't meeting that requirement. We are capturing just the palm, not the entire hand," Blanchard explains.
In some cases the biometric devices that local law enforcement is using to collect data may need to be modified or replaced entirely. "Until this issue gets resolved, the usefulness of the palm database is limited," he says.
Many law enforcement computer systems are now playing catch-up, both for machine-to-machine data sharing between their own booking systems and NGI, and for workstation software that queries the NGI system. For example, the Western Identification Network, used by law enforcement agencies in eight states in the Pacific Northwest, doesn't yet support sharing of the new biometric data, and workstation software used by law enforcement in Seattle to search the new NGI database needs to be updated as well.
Current plans call for these features to be added over the course of next year.
"We are experimenting with workarounds" until the software is upgraded over the next year, says Carol Gillespie, manager of the King County Regional Automated Fingerprint Identification System in Seattle.
Recognizing mug shots
Mug shots have long been a staple of IAFIS, but the FBI's Interstate Photo System Facial Recognition Pilot project, launched in February 2012 in three states, now lets participating law enforcement organizations use face recognition to search against over 15 million of those images. The system returns a ranked list of potential matches. The service will be fully deployed next June.
With IAFIS matching was visual only. Using face recognition algorithms to search for a match against another photo is new; it matches the photo taken at the booking station or from a crime scene with mug shots in the NGI database that have a high probability of being a match.