# A High-Speed Finger Vein Recognition Network with Multi-Scale Convolutional Attention
## 1 Introduction  
With the continuous development of modern society and the ongoing advancement of technology, the security issues surrounding information authentication have received increasing attention. Traditional identity authentication technologies mainly rely on physical identifiers (such as identity cards, keys, access cards, etc.) or knowledge-based identifiers (such as passwords, security questions, passcodes, etc.) for identity verification [1]. However, these methods have many limitations. Not only are they cumbersome to use and prone to being forgotten or lost, but they are also vulnerable to cracking and theft, leading to lower security and inconvenience in terms of portability and management. Biometric recognition technology is a method that uses unique physiological or behavioral characteristics of the human body to authenticate an identity. As an alternative to traditional identity authentication methods, it offers higher security and convenience [2]. In recent years, biometric recognition technology has developed rapidly and is gradually becoming an important component of various organizations' systems and even national security systems. It has been widely applied in various fields of society and holds significant application and research value. Biometric recognition technology can be divided into first-generation and second-generation technologies based on the type of biological characteristics used. First-generation biometric technologies mainly rely on external features and morphological characteristics of the human body, including fingerprints [3], iris [4], and facial recognition [5]. Fingerprint recognition, as one of the most widely used biometric methods, uses compact devices and has a low cost, ease of integration, and quick response times. However, its performance can be greatly affected by finger wear, sweat, or interference from stains, and it is easily stolen through methods like photography or capture, posing a security risk. Iris recognition matches identity based on unique visual characteristics, such as stripes and spots, found in the annular membrane between the pupil and sclera of the human eye. It is highly secure but requires expensive devices and difficult miniaturization, and it necessitates that the device be placed near and aligned with the user's eye, which may reduce user acceptance and provoke resistance. Facial recognition technology has matured significantly and can maintain a high accuracy even with facial coverings such as masks or glasses, but it is highly susceptible to theft and abuse, raising privacy and ethical concerns. For these reasons, there is an increasing demand for biometric technologies that are secure, convenient, and difficult to forge or misuse. Compared to first-generation technologies that rely on external features, second-generation biometric technologies have enhanced anti-forgery capabilities and stability, using internal human characteristics that cannot be directly observed, such as finger vein [6] and palm vein [7]. Finger vein recognition, as a second-generation biometric recognition technology based on physiological characteristics, captures internal vein images of the finger using near-infrared imaging. Under near-infrared light illumination, finger veins exhibit higher light absorption than the surrounding tissues, resulting in a series of distinctive dark patterns in the captured images--these represent the finger vein patterns. Subsequently, through image processing techniques, the vein image is converted into individual biometric data, enabling identity recognition and authentication. Finger vein recognition has the following advantages: (1) uniqueness: The distribution of finger veins is as diverse as that of the iris, with each individual having a unique vein pattern [8]. (2) Stability: since finger veins are located inside the human body, they are unaffected by external factors such as abrasion, moisture, or temperature. Additionally, the shape of human veins remains nearly unchanged after adulthood [9].