Biometrics utilize a person’s biological features for identity verification. Different forms of biometrics have been developed over the years as a response to the need for more secure alternatives to password and passcode-based authentication systems. However, popular forms of biometrics are still prone to being compromised. For example, fingerprints can be lifted from surfaces and replicated, while facial recognition systems can be taken advantage of through deepfakes.
These limitations demand the need for tamper-resistant biometric alternatives, such as vein pattern recognition, which looks beneath the surface to identify individuals.. This method leverages the unique patterns of blood vessels beneath the skin, offering an internal biometric that is more challenging to replicate or steal.
Vein pattern as biometrics
The concept of using vascular or vein patterns as a biometric was first proposed by Dr. Koichi Shimizu in 1992 in a paper where he discussed the potential applications of optical transbody imaging and optical CT scanning. Through the years, numerous research and patents have emerged to continuously improve this technology and make it suitable for various applications.
The principle behind vein pattern recognition
Since veins are beneath the skin, visible light will not be enough to make their patterns recognizable. Instead, this technology uses near-infrared rays (NIR) light emitted by an array of light emitting diodes (LEDs) to illuminate the skin. These rays penetrate the skin and are absorbed by hemoglobin in the blood, making the veins appear as dark structures against the brighter surrounding tissues. A charge-construct device (CCD) camera captures the result and processes it as an image, before being converted into an extracted vascular pattern. This pattern includes data such as vessel thickness and branching angles, and is stored in a database as a digital template for user pattern matching and authentication.
Given the mentioned process flow, arteries can also be used as a blood vessel biometric. However, veins are preferred for this purpose because of their larger size, proximity to the skin, and easier detection. Aside from these features, vein patterns are optimal in terms of their uniqueness across different individuals and relative stability despite aging.
Vein recognition vs. traditional biometrics
Biometric systems are judged on seven factors: how common, unique, stable, accurate, secure, easy to collect, and publicly acceptable a trait is.
A study shows that fingerprints, facial recognition, and vein patterns all score high in universality, uniqueness, and accuracy. However, each faces data collection challenges, fingerprints can be affected by smudges or oily skin, facial scans by masks or facial hair, and vein patterns by lighting, temperature, or health conditions
Vein recognition stands out in two areas: permanence and protection against forgery. Unlike fingerprints or faces, vein patterns are generally stable throughout life and harder to replicate, since veins are hidden beneath the skin. Many systems also include “liveness” checks to confirm the presence of a living person, further improving security.
Despite its advantages, vein biometrics has lower public acceptance, due to its perceived complexity and limited visibility in consumer settings. However, this perception could change as privacy concerns grow and the demand for tamper-resistant biometrics increase. Particularly, hand veins hold great potential for scaled application due to their accessibility and the intuitiveness of the technology for the public. In fact, the global market size for palm vein detection alone has increased from $694.67 M in 2024 to $817.90 M in 2025, with the healthcare segment contributing the maximum market share. The growth of the technology’s application in this sector can be linked to its use for improved patient identification and access control.
An examination of U.S. patenting activity for vein pattern recognition from 2015 to 2023 reveals trends that reflect the evolution of biometric innovations, use cases, and concerns surrounding such technologies.
Vein Pattern Recognition: Patenting Activity
Patent filings peaked in 2018 and 2019, following an already strong showing in the preceding years. These periods of increased patent filing were marked by innovations that aimed to refine vein pattern recognition systems for targeted commercial applications, including retail, banking, and firearm access control.
In 2018, Walmart Apollo filed patents detailing systems for age verification needed for purchasing restricted merchandise, one embodiment using palm vein verification. In 2019, two patent filings by Bank of America on downstream authentication and security analysis involve the use of vein recognition for verifying one-time passwords (OTP). That same year, Rideflag Technologies filed a patent that uses cameras and biometric identification, such as vein pattern, to confirm the identity of vehicle occupants for toll lane compliance.
Other patents were more focused on improving specific aspects of the technology or integrating the technology to multimodal security systems. Accenture Global Solutions, for instance, patented a multi-layered system that includes vein pattern recognition as an additional security layer after initial facial authentication.
The progression of patent filings from 2015 to 2019 can also be attributed to data breach incidents and related issues in the United States. In 2015, a major breach at the U.S. Office of Personnel Management compromised 1.1 million fingerprint records. By 2016, facial recognition came under scrutiny due to concerns about its use in policing and potential racial bias.
Although the patent filings in 2020 onwards are lower, it must be pointed out that the COVID-19 pandemic is significant in increasing the demand for contactless technologies, which is primarily an issue with hand-based biometrics. Issues with facial recognition also arose during this time as people wore masks. Innovations were sought to enable verification that bypasses these issues.
Vein Pattern Recognition: Top Assignees
Companies IDEX Biometrics, United Services Automobile Association (USAA), and Veridium IP lead in terms of the number of vein pattern recognition patents that have been filed from 2015 to 2023. IDEX Biometrics and Veridium IP are both biometrics-based companies, whereas USAA is a financial service and insurance company. The patents filed by Veridium IP were focused on fingerprint based user authentication, with vein pattern as an additional biometric that may be employed. For IDEX Biometrics, their patent strategy was component-based, with patents focusing on certain aspects of biometric machinery such as device architecture, voltage regulation, and smart cards. USAA’s patent applications were more centered on the computer-based processes for biometric authentication.
NEC and Suprema are also long-established players in biometric technologies, with NEC known for large-scale identification systems and Suprema for scanners used in access controls. The patents from Movano, Sports Data Labs, Omnicell, and Bank of America reflect more specialized applications of the technology, respective to the companies’ targets. For example, Omnicell incorporated this form of biometrics into sensor-driven medicine dispensing units. Independent assignee Baldev Krishan is the CEO of IValt Inc. and Smart Embedded Systems, with the former centered on authentication services and the latter for industrial control systems.
Vein Pattern Recognition: Top Law Firms
Leydig, Voit & Mayer tops the list of legal representatives with 11 patents and patent applications. Three of their assignees include Fingerprint Cards, Wells Fargo Bank, and Synaptics. Notably, a number of the law firms listed above have also represented some of the top assignees. For example, Veridium IP has been represented extensively by Leason Ellis, USAA by Fish & Richardson, and IDEX Biometrics by Rothwell, Figg, Ernst & Manbeck.
Vein Pattern Recognition: Top Technology Areas
The top three technology areas align with the core stages of the vein recognition process. The process basically involves the extraction and processing of digital data (G06F) from images that are first detected through recognition techniques (G06V) and then interpreted or read by scanning devices (G06K). There are also technology areas involving image data processing (G06T) and pictorial communication (H04N), which shows developments in the imaging aspects of this biometrics technique.
Other top CPC areas include graphical data reading and recognition (H04L) which suggests innovations in the secure transmission of vein-based biometric data. The presence of classifications such as diagnosis and surgery (A61B) shows that some vein pattern recognition technologies are being explored for medical diagnostics, while time registers and systems for checking (G07C) indicate the application of the technology in access control systems, such as in security checkpoints. This technology is also being actively applied for commercial and administrative purposes (G06Q). Collectively, these reveal the developments in the optimization of the method and the multidisciplinary nature of the applications of vein pattern recognition technology.
Vein Pattern Recognition: Featured Patents
Different forms of vein recognition technologies have been developed to accommodate vein patterns in different body parts. These are supported by a number of patents as described below.
Palm vein pattern recognition
Traditional palm vein recognition systems require users to position their hands at very specific angles and distances to achieve accurate scans. These requirements make the process inconvenient, error-prone, and less efficient in real-world applications wherein hand positioning may be inconsistent for different users. U.S. Patent No. 11,615,639 addresses the problem through an improved palm vein identification apparatus.
The device includes a main sensor that acts as the primary camera for capturing palm vein images. It uses an optical zoom or digital lens to capture high-resolution images at different distances and is mounted on a multi-axis gimbal for automatic repositioning. A secondary sensor detects environmental conditions and tracks the position of the user’s palm. This data is sent to the system, allowing the main sensor to adjust its position for accurate scanning.
With this apparatus, the user’s palm vein pattern can be detected and scanned even through various angles and distances. This improves both user experience and the reliability of this technology for widescale, real-world applications.
The patent titled “Palm vein identification apparatus and method of use” was filed on January 27, 2021 and granted on March 28, 2023 to Keyo with Jackson Klein as the inventor. Legal representation was provided by Eldredge Law Firm with attorney Richard Eldredge listed on the application.
Finger vein pattern recognition
Fingerprint pattern authentication is a popular biometric method due to the accessibility of fingers for quick verification purposes. However, this becomes unreliable when the user’s finger is injured, wet, or compromised in any other way. Similarly, while current finger vein recognition technologies offer more reliability, conventional systems often require high computing systems or are slow in extracting vein patterns, making them unreliable in fast-paced or resource-constrained environments.
To address the issues on current finger vein technologies, U.S. Patent No. 9,558,392 presents a system that uses NIR imaging combined with a level set curvature algorithm to extract finger vein patterns efficiently. When a user places their finger in front of the sensor, NIR light passes through the finger, and a camera captures an image showing the veins as dark lines. The system then processes the image by removing noise, isolating the finger, and identifying vein curves using the algorithm. The final pattern is converted into a simplified vein map for matching, enabling quick and accurate biometric authentication.
The patent “Finger vein authentication system” was filed on February 12, 2015 and published on January 31, 2017. Its current assignees are Korecen Co. Ltd. and Vein Co Co Ltd. The inventors are Bong-joon Park and Chul-joon Park. Legal representation was provided by Nixon Peabody LLP, with attorneys Ronald Eisenstein, Thomas Pavelko, and David Resnick listed on the application.
Eye vein pattern recognition
Biometric systems that use eye characteristics, such as iris or eye-vein patterns, usually require a clear and unobstructed view of the eye. However, in real-life applications, features like eyelids and eyelashes may occlude key areas. These blockages decrease match performance and thus require users to unnaturally adjust their gaze, making the system less user-friendly.
U.S. Patent No. 10,796,147 introduces a method and apparatus that improves the accuracy and usability of eye-based biometric recognition. The method involves capturing an initial eye image, which will then be used as an input to generate multiple synthetic images that simulate different degrees of eyelid and eyelash occlusion. These augmented images will be used to train a classifier capable of recognizing eyes even under obstructed conditions. In the recognition process, the system compares incoming user eye images against the classifier-trained model to compute a match score. Overall, this enhances both the system’s authentication performance and user convenience.
The patent titled “Method and apparatus for improving the match performance and user convenience of biometric systems that use images of the human eye” was filed on February 9, 2018 and granted on October 6, 2020 to its inventor, Keith Hanna. Legal representation was provided by Foley and Lardner LLP with attorneys Gilberto Villacorta, Courtenay Brinckerhoff, and Mark Kassel et al. listed on the application.
The future of vein pattern recognition
Currently, vein pattern recognition is being used in various applications such as healthcare, banking, and government projects, among others. Given its established use cases and potential for innovation, the market for vein recognition biometrics is forecast to attain a valuation of USD 7.46 billion by the end of 2034.
While many veins in the body can be used for identification, hand veins, especially palm veins, are the most practical and widely adopted. Palm vein recognition is at the center of many recent innovations. In January 2025, J.P. Morgan Payments launched Paypad, a biometric terminal that supports both palm vein and facial recognition for payment authentication. Vein recognition is also being integrated into multimodal security systems alongside other biometric methods.
Despite the promising developments for this technology, several challenges remain. First, the cost of implementing and scaling vein recognition systems is still relatively high due to the need for NIR sensors and imaging softwares. The accuracy of the system can also face issues given environmental factors such as lighting, temperature, or physical conditions that affect vein imaging.
Moreover, as with any biometric system, ethical concerns around surveillance and data storage will always be of concern. As mentioned, the current acceptability of the technology is medium, but with the growing awareness of the vulnerabilities in more common biometrics and the innovations that aim to improve security of data, this perception may shift. Nonetheless, these challenges serve as opportunities for innovations that will enable the broader adoption and wide scale use of this biometric technology.
Notes
1 The dataset from which the graphs are derived from specifically mentioned terms synonymous to “vein pattern recognition”. Hence, the data used may not be fully representative of all vein pattern recognition innovations, especially those that use alternative terminologies or those focusing on specific components of the said technology.
