NEC Places First for Accuracy in NIST Testing, Again

  • #1 in Mugshot Identification
  • #1 in Border Security Identification

In an industry fiercely bent towards competition and innovation, we are proud to share that NEC’s facial recognition algorithm again placed first for accuracy in two key categories of the National Institute of Standards and Technology’s (NIST) most recent Face Recognition Vendor Test (FRVT) 1:N Identification.

This builds on two decades of success in which NEC has consistently outperformed the competition in terms of both accuracy and speed, even when faced with demographic differentials like race and sex, or when subjects are wearing facemasks for coronavirus.

The new NIST results published August 5, 2021, showed NEC’s algorithm outperformed the entire field of 291 entries submitted from all over the world on both mugshot identification and border security identification. Our NEC-004 algorithm demonstrated False Negative Identification Rate (FNIR) of just 0.0022 and 0.0345 at a False Positive Rate (FPIR) of 0.003, respectively.

These are the two most important categories for many NEC customers who rely on our technology for law enforcement, immigration, border security, access control for passengers boarding airplanes, for service members at military installations, for employees at government facilities, as well as for visitors of public venues like theme parks and stadiums.

The results from this week were an update to the NIST Interagency report 8271 originally published in September 2019. The major finding of that report was that massive gains in face recognition accuracy had been achieved in the years 2013 to 2018, and these far exceed improvements made in the prior period, 2010 to 2013. Here again today we can see the progress continues for NEC and it reconfirms the ability of face recognition technology to improve the user experience and serve as an effective tool for enhancing security for a wide variety of applications.

Over the last decade, our algorithms have consistently placed at the top of NIST’s ranking on a number of factors primarily due to our massive investments in research and a sharp focus on the needs of our customers. Ensuring algorithms are accurate is essential to helping our customers fulfill their important missions and building public trust in the use of these technologies.

In particular, assessing algorithms’ accuracy across demographic groups is a key component of efforts to mitigate the risk of bias and discrimination. We appreciate NIST’s work in this area and are proud that, when NIST evaluated face recognition algorithms’ performance across demographic groups in 2019, it found that NEC’s algorithm showed “undetectable” false positive error rate differentials across demographic groups based on race and sex.

In the era of COVID-19, NEC also demonstrated the ability to verify identity on subjects even when wearing facemasks. In testing performed by the U.S. Department of Homeland Security (DHS) at its “S&T Rally” conducted last year in Maryland, the NEC algorithms again outperformed all competition in several key categories. In fact, we showed a True Identification Rate of 98.7 percent in scenarios that simulated a boarding gate at an airport with passengers wearing masks.

Throughout many years of NIST testing, the U.S. government has regularly benchmarked the entire facial recognition algorithm market against NEC’s industry-leading results. In 2019, NIST found that 19 companies had caught up to the NEC 2013 algorithm in overall accuracy. In 2020, a handful of companies were able to produce algorithms that met or exceeded NEC’s past performance. Here again NEC is setting a higher bar.

We are especially proud to bring home first place honors in these evaluations because it affirms our mission to serve as a trusted partner to our country’s public servants.

To read more, you can access the full NIST report, linked here.

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NEC Strengthens Its Biometrics Solution by Partnering with Expert Dr. Anil Jain

As a society, we’re increasingly comfortable with cameras being a part of everyday life. They’re built into our phones, hanging over every traffic light, and placed behind most cash registers. Still, for law enforcement, a perfect image of a face can be hard to come by, especially when suspects intentionally try to obscure their identity.

It was this issue that Dr. Anil Jain, distinguished professor of computer science and engineering at Michigan State University (MSU), set out to solve Using a database of unconstrained images – also known as “faces in the wild” because pictures are pulled from sources like social media – Dr. Jain and his team (Dr. Dayong Wang, a postdoctoral researcher, and Charles Otto, a doctoral student) created an algorithm that quickly generates a list of candidate matches to help identify unknown faces from surveillance camera footage or crime-scene images.

NEC recently partnered with Dr. Jain and MSU to license this large-scale face-search system and will use it to enhance its current facial recognition solutions.

“NEC has a very powerful face recognition software called NeoFace that was primarily designed for mug shot to mug shot matching,” said Dr. Jain, “and it has performed extremely well compared to its peers in that kind of scenario. So, they were looking for a solution for the problem where query images have rather large variability in terms of pose, illumination, and expression, and still need to be searched against large face databases.”

“NEC is committed to maintaining its leadership position in facial recognition solutions,” said Raffie Beroukhim, vice president, NECAM’s Biometrics Solutions Division. “In addition to our own continued research, partnerships with academia, in particular Michigan State University, is an important aspect of this commitment. We look forward to the fusion of MSU large-scale face-search algorithm with our industry-leading NeoFace facial algorithms to offer more compelling solutions to address ever-increasing security threats and enhance public and national security.”

“What we provided is a prototype,” said Dr. Jain. “NEC will modify the algorithm that we provided, integrate it with their existing systems, and improve the overall face recognition performance.”

Since joining MSU in 1974, Dr. Jain has received numerous recognitions for his contributions to the field of pattern recognition and biometrics, including his February 2016 election to the National Academy of Engineering (NAE), one of the highest professional distinctions bestowed on an engineer.

Interestingly, he didn’t set out to specialize in biometrics. His career took a turn when the U.S. government engaged Dr. Jain, about 25 years back, to find civilian applications for a government-designed hardware, the Splash 2 processor, that was based on FPGA technology.

“They didn’t tell me to work on biometrics, but the hardware that they provided us made us realize that it was extremely suitable for a generic image processing operation, called point matching, where we extract landmarks from two separate images and put them in correspondence or alignment. And since fingerprint matching is done by using point (minutia) correspondence … it was like serendipity.”

For years, biometrics was primarily used for law enforcement and government applications. Over the past five years or so, we’re seeing more consumer applications of biometrics. We use fingerprints to unlock smartphones. There’s even a facial recognition application that can estimate a subject’s age and gender for targeted advertisements. According to Dr. Jain, the rise of biometrics in our everyday lives has had an element of serendipity as well – where market forces have had to align with high usability and low cost to facilitate adoption.

“Who would have imagined just four years ago that everybody would be using a fingerprint to unlock their phones? Biometrics for mobile devices had been available earlier, but it didn’t really become popular until Apple introduced the Touch ID fingerprint sensor in 2013. This shows that sometimes, even though the technology may be ready, the technology doesn’t lift off unless it’s packaged properly – like Apple putting the fingerprint sensor in the home button.”

Dr. Jain and his doctoral students continue to use their research laboratory to investigate real-world issues and address long-standing research problems. In addition to the large-scale face-search system, recent topics include a study on the persistence of fingerprint recognition accuracy over time and methods to prevent printed photo and replay attacks on a face recognition system.

“We’re really proud of the work we did on fingerprint persistence and face spoof detection because these fundamental problems needed to be answered,” said Dr. Jain. “And these are the issues that need to be addressed for every biometric modality. The impact of the problem is what we keep in mind when we choose which topic to work on. Sometimes, more than technology advancement, we take pleasure in advancing fundamental scientific work.”

NEC is proud to collaborate with visionary leaders like Dr. Jain. NEC already has one of the strongest biometrics offerings available, and as we continue our own research and forge partnerships with biometric leaders, the future of biometrics is something to look forward to.