Vein recognition is a biometric identification technology that offers higher security compared to traditional methods. It works by using hemoglobin in the blood to absorb infrared light, allowing an infrared CCD camera to capture images of the veins in the fingers, palms, and back of the hand. These images are then mapped based on the unique distribution of veins. Advanced algorithms extract specific feature values and store digital vein images in a computer system. When verification is needed, the system captures a real-time vein image, extracts its features, and uses techniques like filtering, binarization, and refinement to compare it with stored data, thereby identifying individuals accurately.
Vein recognition has four main characteristics: high security, ease of use, fast identification, and high accuracy. The probability of two people having the same vein structure is 3.4 billion to one, making each person’s vein pattern unique. Importantly, this internal information is not affected by factors like skin damage or environmental conditions. Additionally, vein recognition requires living body detection, meaning the finger must be alive for the system to work.
According to Sun Zhenan, a researcher at the Chinese Academy of Sciences and a member of the Pattern Recognition Committee of the China Association of Artificial Intelligence, vein recognition relies on the absorption of near-infrared light by hemoglobin in subcutaneous veins. This creates a black-and-white contrast image, where veins appear dark and surrounding tissues appear lighter, allowing clear visualization of the vascular structure.
Unlike fingerprint recognition, which depends on dryness or cleanliness of the finger, vein recognition is unaffected by wet, dirty, or damaged fingers because it scans beneath the skin. Also, no physical contact is required during the process, making it quick—often taking just one or two seconds.
Currently, vein recognition is mainly applied to fingers, palms, and the back of the hand. As Sun Zhenan explains, near-infrared light easily penetrates the skin to image these areas, while other parts of the body have less dense veins, making imaging more challenging.
Palm vein recognition involves capturing an image of the palm using an infrared-sensitive camera. The resulting image is processed digitally to create a vein pattern, which is then matched against a database using complex algorithms to identify an individual.
Finger vein recognition is another form of this technology. A finger vein map is created using a specialized instrument, and feature values are extracted through comparison algorithms. The system stores these digital images in a computer for future verification.
Finger vein recognition is internationally recognized for its uniqueness, comparable to retinal scanning, with a false rejection rate of less than one in ten thousand and a false acceptance rate of less than one in 100,000.
Hitachi pioneered finger vein authentication in 1997, and by 2002, they released the first commercial system. However, due to higher imaging costs, it hasn't become mainstream. Companies like Zhuhai Yi have made progress in reducing costs and improving applications.
While palm vein recognition has slower speed due to large image databases, finger vein recognition offers faster processing and high precision. Each has its own advantages depending on the application. For example, finger vein systems are better suited for mobile devices, while palm vein systems offer higher security but are less convenient for integration.
In December 2015, the central bank issued a notice requiring the use of biometric features alongside real-name systems. In January 2016, major banks collaborated with Guangdian Express to draft financial industry standards for vein recognition. By March 2016, college entrance exams began collecting biological traits such as finger veins to prevent impersonation.
The national standard GB/T 33135-2016 was officially released in May 2017, setting general specifications for vein recognition systems. In November 2016, Guangdong Social Security introduced standards for vein-based pension verification.
Future trends include applications in prison management, education, social security, and banking. Finger vein access control systems can enhance security in prisons, reduce fraud in exams, and improve safety in financial institutions.
In self-service banks, finger vein authentication replaces passwords, preventing theft. Bank vaults use vein recognition to ensure only authorized personnel enter. Cashier areas use it to control access and monitor staff. Data security benefits from the non-replicability of vein patterns, offering greater protection than traditional keys.
Prison access control systems are part of China's "Golden Shield Project," aiming to modernize security and prevent internal breaches.
Leading vendors like Tongyuan Micro-Intelligence and Fujitsu offer advanced solutions. Tongyuan provides intelligent terminals with high security and accuracy, while Fujitsu specializes in palm vein technology used in banking and public sectors.
Easy Times Technology develops open modules for access control, locks, and attendance systems, widely used in education, healthcare, and finance. Shenzhen Pulse Technology focuses on finger vein hardware, including collection and recognition modules.
Overall, vein recognition continues to evolve, offering secure, efficient, and reliable identification solutions across various industries.
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