Each person's body and behavior contain unique information, and biometric technology uses computers and high-tech instruments to collect images, convert them into multimedia such as graphics, voice, and video, extract unique personal characteristics, and store them in a database.
 
  The potential benefit of multi-biometric solutions is the ability to extend to the acquisition of sensitive data by accessing the human body to controlled areas. This makes biometric identification systems more secure, as it becomes virtually impossible for intruders to simultaneously deceive multiple biometric signatures using artifacts or imitations, and individuals can flexibly switch to other signatures if one is inconvenient.
 
  Multi-biometric identification refers to the integrated application of multiple biometric technologies, offering higher performance, reliability, and security than individual technologies. While individual technologies have limitations in their characteristics and advantages, multi-biometric identification involves acquiring various biometric data through different acquisition devices and then integrating them into a complete system using either independent recognition algorithms or a unified fusion algorithm. This system verifies whether the feature value matches a pre-stored template in a database, completing the identification and verification process. This provides users with multiple options during identification and offers higher security than using a single biometric technology.
 
  The AND and OR operations in multi-biometric authentication
 
  Currently, the mainstream single-item technologies include fingerprint, face, iris, and vein (vein is a new application technology); the core structural principle of multi-biometric identification technology is an "AND" relationship or an "OR" relationship? The difference between the two lies in how to analyze and judge these feature values.
 
  If it's an "OR" relationship, it means that after establishing a multi-biometric identification system software platform, various biometric data, such as fingerprint images and facial images, are acquired through different collectors. Then, each data type is determined using its own independent mathematical equation (i.e., a "recognition algorithm") to determine whether the fingerprint or face matches a pre-stored template in the database. Different biometric algorithms are used to process different biometric features, each yielding independent results (e.g., a fingerprint recognition algorithm analyzes a fingerprint, and a facial recognition algorithm analyzes a facial image, each providing a fingerprint comparison and a facial comparison result). If one recognition algorithm fails to obtain a clear identification result, another algorithm can be used for confirmation.
 
  If the relationship is one of "AND," then it refers to "fused biometrics," which represents the latest trend in the field of multi-biometrics. Fusion biometric systems also use a single sensor that combines various independent or multiple acquisition methods to collect different biometric features (such as fingerprints, facial images, iris scans, etc.). These collected biometric features are then processed uniformly using a fusion algorithm, and the final identification result is derived based on a comprehensive judgment of the multiple biometric technologies. This processing method and result are faster, more accurate, and have better system scalability, ultimately elevating the entire system to a new level of security.
 
  Performance Comparison of Various Biometric Technologies
 
  Currently, fingerprint recognition, facial recognition, and iris recognition are the mainstream biometric identification methods, while vein recognition, as a newer method, offers higher security. Among these methods, what are their advantages and disadvantages? Which is superior? A performance comparison will reveal the secrets.
 
  Fingerprint recognition: the most widely used and most mature technology.
 
  Fingerprint recognition refers to identifying individuals by comparing the detailed features of different fingerprints. Because everyone's fingerprints are different, and even among the ten fingers of the same person, there are obvious differences, it can be used for identity verification.
 
  The fingerprint recognition technology used in our second-generation ID cards has the advantages of being convenient, widely used, and well-recognized. However, like many movie plots, fingerprints are easily stolen and copied, resulting in low security. Furthermore, fingerprint features are unstable; peeling skin, calluses, and varying moisture levels can all affect their accuracy. During the second-generation ID card collection process, many groups, such as farmers and workers, experienced problems with fingerprint collection. While fingerprints leave traces everywhere, which is advantageous for police investigations, their ease of copying also facilitates counter-surveillance.
 
  Facial recognition: Convenient for data collection
 
  Facial recognition technology is a biometric identification technology that uses facial features to identify individuals. It involves using a camera or webcam to capture images or video streams containing human faces.
 
  It automatically detects and tracks faces in images, then performs a series of related techniques on the detected faces, including face image acquisition, face localization, face recognition preprocessing, memory storage, and comparison and identification, to achieve the purpose of identifying different people. Face recognition technology is currently a highly regarded biometric technology, and face images are easier to acquire. However, because faces are three-dimensional, they are greatly affected by lighting, expressions, body shape, hair, and movement. Furthermore, because they are surface features, they are easily forged and copied. Therefore, their stability and security are relatively low when used for identity verification and criminal investigation. If the technology makes breakthroughs, it could be widely applied in fields such as public security.
 
  Iris recognition: relatively accurate
 
  Iris recognition technology is an identification technology that utilizes the texture features of the iris of the human eye for identity verification. The iris is a fabric-like ring of various colors within the pupil of the human eye. Each iris contains a unique structure based on features such as the corona, lens, filaments, spots, structures, dimples, rays, wrinkles, and stripes. It is claimed that no two irises are the same. Technically, iris recognition is relatively accurate, but in practice, it requires illuminating the eye with infrared or visible light to obtain an image. User cooperation is low, and there is a high degree of psychological resistance, making it unsuitable for large-scale applications such as ID cards. Furthermore, products such as colored contact lenses on the market can alter the characteristics of the iris, making it relatively easy to replicate. Iris recognition technology is currently being used in various fields in my country, including attendance tracking for coal miners, prison inmate management, bank vault access control, border security checks, military security systems, and student identity verification.