With the continuous maturation of fingerprint technology and the gradual reduction in R&D and production costs, fingerprint recognition technology-related products are poised for a period of rapid development.
 
  Fingerprint Recognition Principles
 
  With the advent of emerging technologies such as mobile internet and the Internet of Things, traditional methods of human authentication are no longer sufficient to meet the needs of social development. The trend is towards using high-tech methods, such as computers, optics, acoustics, biosensors, and biostatistics, to identify individuals based on their inherent physiological characteristics (e.g., fingerprints, facial features, irises) and behavioral features (e.g., handwriting, voice, gait).
 
  Currently, the main biometric methods include fingerprint recognition, palmprint recognition, iris recognition, facial recognition, DNA recognition, and behavioral recognition.
 
  Of these, fingerprint recognition is currently the simplest, most practical, most accurate, and best-developed method. Globally, fingerprint recognition accounts for nearly 60% of the entire biometric market, with thousands of fingerprint recognition manufacturers producing hundreds of different fingerprint recognition products, while other biometric technology manufacturers account for less than one-tenth of that.
 
  The most common applications of fingerprint recognition are fingerprint attendance and fingerprint access control. However, with the advent of the mobile internet, including information security and mobile payments, there is a significant demand for biometric authentication. Fingerprint recognition has become a widely accepted method by mainstream smart device manufacturers and consumers. On the eve of the mobile payment boom, fingerprint recognition based on smart terminals is poised for explosive growth.
 
  A typical fingerprint recognition system should include: a fingerprint recognition sensor, a feature extraction/matching module, a feature template library, and application software. Fingerprint matching can be divided into two steps: first, extracting the features of the fingerprint to be verified; then, comparing its similarity with template fingerprints in the fingerprint template library to determine whether the two fingerprint images come from the same finger.
 
  We can see that the core of fingerprint recognition is accurate and efficient fingerprint acquisition and analysis. The development of fingerprint recognition acquisition technology can be broadly divided into three methods: optical recognition, capacitive sensors, and biometric radio frequency.
 
  1. Optical Recognition
 
  Optical recognition is an earlier fingerprint recognition technology. It relies on light emitted by an optical transmitter, which hits the finger and reflects back to the machine to obtain data, which is then compared with a database to see if they match. Optical fingerprint recognition can only reach the epidermis, not the dermis, and is greatly affected by the cleanliness of the finger surface.
 
  2. Capacitive Sensors
 
  Capacitive fingerprint recognition uses two capacitors spaced at intervals. The fingerprint's texture (convexity and concavity) is utilized; as the finger glides across the fingerprint sensor, the current to the two capacitors is switched on or off to detect the fingerprint data. Capacitive sensors require relatively clean fingers, and the silicon material used in the sensor surface is relatively easy to damage. Technically, capacitive fingerprint recognition technology is supplied by companies such as Authentec, Validity, and FingerprintPrintCardsAB (FPC). Authentec was acquired by Apple, and Validity was acquired by Synaptics. Capacitive fingerprint sensors are currently the most widely used technology.
 
  3. Radio Frequency (RF) Sensors
 
  RF sensors emit a small amount of radio frequency signal to penetrate the epidermis and obtain information about the inner fingerprint ridges. This method has lower requirements for finger cleanliness. RF is a relatively new technology and is a type of capacitive fingerprint sensor, but it is limited by patent issues. RF is the future direction of development.
 
   Fingerprint Recognition Acquisition Methods
 
  Regardless of the acquisition technology used, from the user's perspective, there are two acquisition methods: pressing and swiping.
 
  1. Swiping
 
  The finger is swiped across the sensor, and the system acquires the fingerprint of the entire finger. When the finger is pressed down, a complete image cannot be acquired at once. During acquisition, the finger needs to swipe across the acquisition surface, and each fingerprint image captured at that moment is snapshotted. These snapshots are then stitched together to form a complete fingerprint image.
 
  The advantages of swiping are low cost, easy integration, and the ability to acquire large-area images. It uses traditional feature point algorithms. However, the disadvantage is that it requires a continuous and standardized action from the user to acquire the image, resulting in a poor user experience. Its application and promotion have not been very successful in the past.
 
  2. Pressing
 
  The finger is placed flat on the device to acquire the fingerprint image. Generally, to obtain the fingerprint of the entire finger, a sensor larger than the finger must be used, and the entire finger is pressed onto the sensor simultaneously.
 
  The advantages of press-type fingerprint recognition are a superior user experience; a single press captures an image, aligning with user habits on mobile applications and requiring no user training. Disadvantages include higher cost, greater integration complexity, a relatively small image area captured per press, insufficient feature points, and the need for complex image comparison algorithms for recognition.
 
  Clearly, from a user's perspective, press-type fingerprint recognition is the simplest and most convenient. More and more mobile devices will adopt press-type fingerprint recognition solutions in the future.
 
  Currently, mobile phone manufacturers, internet companies, mobile operators, UnionPay… all are accelerating the development of mobile payments, and fingerprint recognition is poised for significant growth.