NEC is a pioneering company that has been leading the way in biometric authentication technology for almost half a century. Operating on a global scale, our technology is setting the standard in more than 70 countries around the world where to date we have deployed more than 700 systems. Our worldwide presence can be attributed to the superior precision of our products, which are ranked number one in the world. NEC’s fingerprint, face, and iris recognition technologies have been ranked first in benchmark tests conducted by the United States National Institute of Standards and Technology (NIST). In addition to our three primary biometric technologies, we also have finger vein, voice, and ear acoustic recognition technologies, which can be combined to create powerful multimodal biometric solutions. As one of the world’s leading vendors of biometric technology, NEC will continue to strive for the achievement of safety, security, efficiency, and equality.

Digitization and big data are rapidly transforming the world, making it possible to offer each individual services and solutions tailored to their specific needs, a trend that will become ever more pervasive in the future. Key to the seamless integration of this technology in society — so that people can enjoy its benefits without worrying about security or access — is the use of biometrics, an authentication technology that identifies individuals based on physical and behavioral characteristics peculiar to that individual. In this paper we discuss Bio-IDiom — a biometrics brand launched by NEC in April 2018 — which can give us an idea of what that future society might look like. We also examine how multimodal biometrics can offer advanced safety and reliability by combining multiple biometric authentication technologies. Finally, we introduce some actual case studies where our multimodal biometric authentication solutions have been applied in real world conditions by our customers and partners.

In this paper, we will discuss the future evolution of biometrics — a rapidly evolving technology that has become a part of most people’s everyday life. We begin with the assumption that biometrics will evolve in the direction of increased efficiency, introducing a number of case studies that focus on how biometrics can increase efficiency — including efficient manipulation of massive amounts of data, efficiency in terms of “things”, and efficiency in the real world. We also assume that biometrics will become a reliable way of measuring people’s mental states and look at some case studies which point to future developments in this area, from targeting and understanding specific individuals to targeting and understanding groups. Finally, we will look at AI technology and how biometrics can be used as a driver to enable exponential growth that will lead to future sustainable growth in the economy.

The Japanese Act on the Protection of Personal Information updated and enforced in 2017 makes it clear that individual identification code such as DNA, facial feature quantities and iris information are to be classified under personal information. Similarly, mainly in Europe and North America, respects for of human rights and privacy are needed for human surveillance and tracking technologies at a worldwide scale. In this paper the author reviews the privacy measures of the biometrics businesses for which careful discussions are required, as based on efforts currently being applied by NEC.

The Western Identification Network (WIN) is a not for profit corporation in the United States, providing a multi-state, multi-modal, biometrics identification system. Formed in 1988, WIN created a revolutionary concept: gaining the backing of governors, attorneys general, legislators, and chief law enforcement officials to combine technical and financial resources enabling the first multistate biometric network sharing fingerprint data across state lines. The outcome was the formation of WIN, providing identification services for criminal and civil identification purposes.

The “My Number Card” is the IC card delivered by Japanese local governments to applicants in accordance with the “Act on the Use of Numbers to Identify a Specific Individual in Administrative Procedures”. The “My Number Card” carries the face photo data on the front side and inside is the IC chip for use in various operations. This paper outlines NEC’s “Face Recognition System for use at the My Number Card Delivery Counters” that is used at the time of the card delivery. Experiments demonstrating the utilization of the card’s face photo data are also introduced.

Since 2017 NEC has been providing “NeoFace Cloud”, a face recognition cloud service using the high accuracy NeoFace engine. NeoFace Cloud features the benefits of cloud services at a reasonable monthly fee. Such benefits increase the applications of face recognition services, even in locations that are unsuitable for installing and managing the servers. These include outdoors or in facilities not attended by system managers. “NeoFace Cloud” is increasingly being adopted by customers for linking face recognition to their business systems or services. This paper introduces the technical points of the said service.

Acceleration of digital transformation using video analytics technologies in stadiums, shops, hotels and public transport has made it necessary to provide the efficient provision of composite video analytics solutions. NEC Enhanced Video Analytics (EVA) is an integrated software platform that flexibly combines the components of video analytics including face recognition, behavior detection and attribute estimation to meet the needs and resolve the issues of customers. This paper introduces the advantages provided by this platform, some examples of solutions and details of the system configuration.

As e-commerce strengthens its hold on consumers, brick-and-mortar stores are being forced to rethink the way they do business. The need to create a customer experience that’s unique, fresh, exciting and cannot be reproduced in the virtual world is leading to the launch of future-type stores that leverage the power of information technology to enhance the customer shopping experience smoothly, while offsetting potential labor shortages. To meet that trend, NEC has been using biometric technology. We develop systems to streamline store entry and payment, reducing or even eliminating waiting time at checkout. Such a system would offer more than just a new level of convenience, it would fundamentally transform the retail world and pave the way for biometrics to become a key part of everyday life in the 21st century. In this paper, we will show what such a system would look like, explain how it would work, and reflect on the profound changes it could generate in our society.

The amendment of the Act on the Prevention of Transfer of Criminal Proceeds on 30th November 2018 made possible the completion of the online identification of bank account-opening customers that is obligatory for the financial institutions. Personal identification used to be carried out by forwarding non-transferrable postal mails to customer homes which takes quite a time. The online possibility of identification, now allows users to use a desired financial service immediately. To deal with the online account opening facility, NEC provides a Personal Identification Service making use of its world leading face recognition technology (face matching and impersonation prevention) to support the improvement of user experience and the promotion of digital businesses in financial institutions.

Recently, following the rapid increase of foreign visitors to Japan and of the enhancement of the value of their everyday activities, the demand for service industries such as hotels and theme parks has tended to increase. On the other hand, the increased labor market shortages has made it an urgent issue to reduce any burdensome effects on operations in those industries. To achieve the targets both of reducing the burden on service providers and of improving the customer satisfaction of users, a technology is sought that can recognize the identity of each user “quickly” and “accurately”. The face recognition technology of NEC enables simple registration and rapid and accurate personal identification by means of non-contact authentications. This paper introduces face-based solutions for use in hotels and at public attraction venues as well as supporting future plans for connecting customer journeys by universally applying face authentication IDs.

In a construction site, the field supervisor manages the site and personnel with skills in various expert techniques are organized to advance the work. As the required techniques vary depending on the operation process, personnel belonging to several companies enter and exit from the site during the construction period. Since some of the field operations are dangerous, the supervisor must secure the safety of each worker by identifying all of the workers on the site and managing their data. NEC has implemented a service that performs these management procedures with face recognition-based personal identification and the location information without installing additional equipment. Thanks to the capability of easily obtaining the entrance/exit data, this service can check the credentials of each worker and output the results of entrance/exit data calculations. This paper introduces the features of this service.

Recently, the fields of “monozukuri”, or fabrication of goods, have seriously called into question whether or not the work is being executed correctly as defined in law and in the agreements made with customers. In addition, as the fluidity of human resources is increasing, as seen in the proposed increase in the number of foreign workers, it has become necessary to manage workers appropriately in order to improve the quality of their work by identifying them individually. This paper introduces the personal identification of individual field workers, based on the facial recognition of individuals and of the “NEC DX Factory Co-creation Space,” that are implementing the next-generation fabrication process. Actual cases of its use and the importance of personal identification in the field of “monozukuri” are also discussed.

To boost security and enhance convenience, many public facilities such as airports and train stations are beginning to roll out new face recognition technology, with many more already planning to implement it. On a more mundane level, this new technology is poised to replace passcodes and ID cards in applications such as payment verification, mobile phone access, online shopping, and so on. In this paper, we will look at the face/human body detection and face matching technologies introduced by NEC, as well as person re-identification technology which complements face recognition. Person re-identification technology is another form of biometrics that can identify an individual based on their overall appearance, even when their face is not visible. We also review the test results of the Face in Video Recognition (FIVE) program conducted by the United States National Institute of Standards and Technology (NIST) in which NEC was ranked first in evaluation accuracy.

Iris recognition is already beginning to penetrate the public sphere and has recently been adopted in smartphones, national ID systems, and border control. This paper outlines iris recognition technology in general and introduces the key elements of NEC’s iris recognition technology — in particular, fusion matching technology which is playing a pivotal role in taking the precision of iris recognition to the next level. We will also review the results of the iris recognition evaluations conducted by the United States National Institute of Standards and Technology (NIST), which demonstrate unequivocally the superior precision of our technology. Finally, we will examine the latest trends in iris recognition technology.

For more than a century, latent fingerprints have been one of the most important forms of evidence used by law enforcement and criminal investigative agencies worldwide. While tremendous progress has been made in conventional fingerprint matching, matching latent fingerprints has proven to be a more difficult problem due to the poor quality of the prints. Typically obtained under less than ideal conditions, latent prints are frequently incomplete or degraded by background noise. Since fingerprint identification depends on the quality of the print, matching technology with much higher accuracy is required to identify suspects, increase the arrest rate, and help build a safer and more secure society. NEC has been working on fingerprint recognition for nearly fifty years, constantly striving to increase the accuracy of our matching technology. This paper provides a historical overview of NEC’s research in fingerprint matching technology and introduces our latest technological advances in this field.

We use our voices all the time to communicate with one another. Talking is the simplest and easiest means of information transmission. It could also be one of the simplest means of identification. Recent advances in computing technology have made voice recognition — a biometric technology based on the unique characteristics specific to an individual’s voice — more convenient, safer, and more secure than ever. In this paper, we review the current state of voice recognition technology and show how deep learning — the core of contemporary AI technology — is providing the key to unlock the power of biometrics. We will also look in some detail at NEC’s work in the field of voice recognition technology, which is at the forefront of worldwide efforts to make this technology accessible and reliable. Finally, we discuss potential industrial applications for voice recognition technology such as public safety solutions.

Just as each face has its own unique characteristics, so too do other parts of the head. The ear, for example, has many distinct features, including the shape of the ear canal. Ear acoustic authentication is a new biometric technology that identifies the shape of the ear canal using an earbud-type recognition device to measure reflected sound inside the ear. Authentication is possible at any time or place simply by having subjects listen to the sound. It is also possible even if the subjects are wearing gloves and masks. Combining this technology with hearables — emerging ear buds with advanced computing — makes possible a hands-free, eyes-free connection to AI, increasing the power of ICT to enhance human potential.

Today surveillance cameras are becoming ubiquitous in public facilities such as shopping malls, office buildings, airports, and train stations. Until now, these cameras have typically only been used post-incident to support criminal investigations. However, the threat posed by criminal actions such as terrorist attacks is growing, which can cause serious damage or loss of life. Such an event is focusing attention on taking advantage of these tools to prevent incidents from occurring in the first place. This paper introduces new technology based on NEC’s “Profiling Across Spatio-Temporal Data” technology that can classify an individual and assess their threat potential. By performing high-speed extraction of frequently appearing individuals and analyzing the results, this technology can classify the behavior patterns exhibited by these individuals — such as loitering, passing through, and standing still. The hope is that this technology will help prevent crimes by identifying suspicious individuals and alerting security personnel before an incident can occur.

This paper introduces NEC’s drowsiness estimation technology based on facial video data. This system can operate on low-end IoT devices that use fewer computation resources. Drowsiness in humans is clearly expressed via changes in facial expression — especially changes in eyelid movement — and can be determined with high accuracy by capturing the closing duration of the eyelids and the increase in blinking rate. In order to capture fast blinking, however, it is necessary to precisely extract the movement of the eyelids. This bears a heavy computation cost. NEC has developed a method to capture slowly fluctuating eyelids (eyelid variability) as a sign of drowsiness, which makes it possible to accurately determine drowsiness even with eyelid movements extracted with only one third the detail of conventional methods. Since this system can easily be installed and operated on low-end devices, it should be applicable across a broad range of scenarios.