A team of engineers introduced a new biometric authentication system that can automatically collect, categorize, and store data utilizing much less computational resources than original methods. Here’s why this is a major advancement in the sector and how it could affect everything from how you log in to your electronic devices to how your doctor approves your next insurance claim.
Biometric Authentication
When you hear of biometrics, you may think of advanced retina scanners or face recognition systems. However, the science of recording individual traits and utilizing them for authentication purposes is as ancient as civilization itself.
Ancient cultures like the Babylonians utilized fingerprints to seal certified clay tablets as far as 500 BC. By the 1800s, a fingerprint recording system was introduced to the legal system in India. This system, named after its creator, Inspector General Edward Henry, is still in use globally today.
The introduction of technology has transformed biometrics from a security service used by governments and conglomerates to a method that anyone can use to protect their belongings, data, and more. Today, biometrics offers a fast, password-free solution. As such, its popularity is on the rise.
Types of Biometric Authentication
There are two main types of biometrics in use today: external and internal. Both types of biometric data offer users advantages and disadvantages that make one better suited for a particular application than the other options.
External Biometric Authentication
Most people think of external biometrics when discussing this tech. You have seen or used these systems, even if you were unaware of your participation. These options include items like the fingerprint and face scanner found on today’s advanced smartphones.
External biometrics offers fast access and authentication from a distance. These networks are ideal when you need to monitor a large area or pick out a person from a crowded city. Today, biometrics networks like the facial recognition system used in China enable it to autonomously keep tabs on its citizens, catch wanted criminals, and provide access to sensitive data.
Problems with External Biometrics Today
There are several scenarios in which external biometric systems fall short. For one, they rely on easily visible characteristics like your face or fingerprint. These items can be gathered and used to spoof the system. Already, there have been considerable studies documenting how people were able to hack facial recognition systems simply by using photos of the individual.
Internal Biometric Authentication
These drawbacks have led many to seek out a better alternative, such as internal biometrics. Internal biometrics are based on your internals, like tissue measurements, vein layout, and other vital human traits that are unique to each individual.
The advantage of internal biometrics is that they are invisible to observers. It’s much harder to get an internal scan of someone’s vein network in their palm versus a picture of their face. Additionally, it is very hard to replicate this data even if you have generalizations about it. As such, internal biometrics provide high accuracy and additional fraud resistance.
The most common ways that internal biometrics are captured is through the use of optical coherence tomography (OCT) and photoacoustic tomography (PAT). The OCT approach creates a topographic map of tissue measurements, while the PAT method takes precise finger measurements.
Hyperspectral Imaging
The most advanced way to obtain internal biometrics currently is to utilize hyperspectral imaging. This method of photography creates images by blasting the palm with visible to near-infrared wavelengths with 5-nm resolution. The result is an image that reveals data across a broad spectrum of contiguous wavelengths.
Osaka Metropolitan University in Japan
Hyperspectral imaging offers a variety of advantages over traditional scanning methods. For one, every wavelength reveals different aspects of the palm’s internal structure. As such, a single scan can provide a multitude of potential password material.
Problems with Hyperspectral Imaging
Hyperspectral imaging offers some of the best security options to the market, but it has some flaws that have slowed its integration on a large scale. For one, it’s much harder to administer this style of biometric security as it requires a person to sit down and have their palm scanned directly.
This approach will work for sensitive areas but would be too time-consuming to utilize in a massive or city-wide scenario. Imagine having to wait for every subway passenger to scan their palm before you could enter the train. The added wait and delays would nullify any security benefits.
Massive Data Requirements
One of the main reasons hyperspectral imaging hasn’t seen massive adoption is due to the sheer size of each scan. Image size can affect a lot of aspects of your security. Storing someone’s palm or fingerprints doesn’t require any space and can be done on everything from paper to a digital system.
In comparison, a hyperspectral image contains a variety of in-depth data across varying wavelengths, resulting in a massive file packed with data. This added data makes it harder to examine as there is much more to review if you are looking for patterns or comparing data.
Biometric Authentication Study
Recognizing the inherent limitation of this approach and the tech’s potential, a team of engineers from Osaka Metropolitan University in Japan released the study called “Identification using a cross-sectional hyperspectral image of a hand.”1 This research paper delves into a novel method to reduce the amount of data required to utilize hyperspectral scans for security purposes.
The engineers demonstrate a system that can generate a cross-sectional image of a part of the palm that provides high spectral resolution and can identify key details like distinct vein patterns. They also reveal how this new system has the potential to enhance personal identification moving forward across multiple industries.
The Upgraded Biometric Authentication System
The engineers captured hyperspectral images accurately and then sliced them into smaller files that are better suited for verification, storage, and transfer. The system integrates a special camera, lighting, a scanner, and computer algorithms to accomplish this task.
Hyperspectral Camera
At the core of the experiment was the hyperspectral camera (NH-A-S, EBA, Japan, Japan). This device was set up with an f=12mm, M118FM12 single-focus lens that provided a spectral resolution of 5 nm across varying ranges from 400 to 1000 nm.
Palm Scanner
A sensitive palm scanner was set up to capture the vein network and internals of the palm during the process. The scanner featured a 240×240-mm scanning area, allowing it to capture a specific region of the palm. Notably, the unit sat 900 mm above the floor and was tilted at an angle of ∼30 deg to the ground.
Illumination
Lighting was used to illuminate the palm and provide depth to the images. Specifically, a 500-W halogen lamp was placed beneath the scanning section that shined onto a 5-mm-thick high-transparency glass plate. The plate was selected due to its ability to transmit visible to near-infrared light with minimal loss.
Personal Computer
Notably, this system can function on a traditional PC. For this experiment, the engineers utilized a laptop computer that had an Intel Core i7-1068NG7 and 32 GB of RAM. It had no problem storing hyperspectral cube data.
Artificial Intelligence
A purpose-built AI algorithm serves multiple roles in the system. For one, it’s tasked with determining the best region of interest (ROI). The ROI is an area of the scan that offers the clearest and most personalized info.
The AI would take this data and create a hyperspectral cube image. Then, it would compute the ideal cutting plane based on Google’s MediaPipe Hands, a machine-learning library.
This approach eliminated the need for engineers to create a new image registration library, saving money and time. The results are a 2D spatial-spectral image that provides distinct identifying parameters.
Biometric Authentication Test
To test their theory, the researchers selected 10 healthy adults ranging in age between 24 to 47 years old. Each subject had their palm hyperspectral scanned multiple times throughout the preset time period. Notably, each participant was on a unique scanning schedule which allowed engineers to account for variables that occur based on time and other factors.
Notably, a 500-W halogen lamp was placed beneath the scanning section to illuminate the subject’s palm from the reverse side of the glass. From there, the scanned internal data was processed utilizing different software packages including Jupyter Notebook, LabVIEW, and ImageJ.
Biometric Authentication Test Results
The test results reveal a major success. The engineers achieved reliable identification based on this data on all test subjects. Interestingly, they noted that the system was able to provide better results with a smaller scanned area. Additionally, they found that cross-sectional hyperspectral images of the palm provided different features at each wavelength, enabling multiple layered observation and authentication.
Biometric Authentication Benefits
There are a lot of benefits that this technology will bring to the market. For one, it will help make biometric systems safer and more efficient. In order for biometrics to expand in the market, the technology needs to overcome some of its primary weaknesses. This latest approach helps to fill a void in the sector and promises to provide high security with minimal costs.
Biometric Authentication Applications
There are several potential applications for this technology ranging from the commercial sector to the medical and military uses. The ability to quickly and accurately authenticate a person is crucial to many industries, here are just a few potential applications for this technology in the future.
Security
The most obvious use of these systems is to upgrade security. In the future, your palm print may be how you make offline payments, access your home, or even start your vehicle. As such, it’s vital that these systems be as accurate and accessible as possible.
Medical
The medical sector could leverage this technology to ensure the identity of their patients. From malpractice to fraud and simple human errors, the medical sector is in need of a way to efficiently verify a person’s identity before they provide them with healthcare. This system could offer an affordable alternative that could prevent misdiagnosis and other errors that result in losses and unnecessary suffering.
Biometric Authentication Study Researchers
Takashi Suzuki led the hyperspectral study. He worked with a team of engineers and scientists from Osaka Metropolitan University in Japan. Now, the team seeks to expand the technology’s use case scenarios and create more affordable and accessible methods to obtain and integrate the technology on a large scale.
Innovative Companies Leading the Biometrics Market
There are a lot of firms that currently have some form of R&D revolving around biometrics. From companies seeking to utilize your retina to access your crypto account all the way to retina scanners used to keep your prized positions locked away, there is no shortage of manufacturers involved in the market. Here’s one company that has put forth considerable effort to create a reliable biometrics system to enhance their ROI and UX.
Alibaba Group Holding Limited (BABA +4.59%) entered the market in 1999 to connect merchants and consumers via a digital marketplace. The company has since grown into one of the largest online e-commerce providers in the world by volume. Today, it has hundreds of millions of active users and connects thousands of merchants to clients daily.
Alibaba has been quietly working on a biometric pay system since 2004. The system, dubbed “Smile to Pay”, uses facial recognition to allow users to make payments. Although it’s still in its beta testing stages, company executives stated they hope to utilize the tech to authorize payments from the AliPay wallet simply with a face scan.
Alibaba Group Holding Limited (BABA +4.59%)
Alibaba is a massive e-commerce site that has clients and partnerships with some of the largest tech giants in the world. Its positioning and access to a massive network of clients and merchants make Alibaba well-suited to integrate any biometric solutions with success. As such, BABA is worth further research.
Latest on Alibaba Group Holding
Never Forget Your Keys Again – Biometric Authentication
The drive to utilize biometrics is on the rise globally. Corporations, consumers, and governments are all pushing this technology. Impressively, this latest development offers a reliable and effective way to improve results, lower storage and computational costs, and provide reliable security. As such, this work could have an upending effect on the market moving forward.
Learn About Other Cool BioTech Today.
Studies Referenced:
1. Suzuki, T. (2025). Personal identification using a cross-sectional hyperspectral image of a hand. Journal of Biomedical Optics, 30(2), 023514. https://doi.org/10.1117/1.JBO.30.2.023514