Fingerprint recognition Fingerprints, due to their lifelong immutability, uniqueness and convenience, have become almost synonymous with biometric identification. Fingerprints refer to the uneven lines on the skin on the front of a person's fingertips. The lines are arranged regularly to form different patterns. The starting point, end point, junction point and bifurcation point of the lines are called the minutiae of the fingerprint. Fingerprint recognition refers to identification by comparing the detailed feature points of different fingerprints. Since each person's fingerprints are different, there are obvious differences between the ten fingers of the same person, so fingerprints can be used for identification. In fact, in ancient my country, fingerprints (handprints) have long been used to sign documents. In 1684, plant morphologist Grew published the first scientific paper on fingerprints. In 1809, Bewick used his fingerprint as a trademark. In 1823, the anatomist Purkije divided fingerprints into nine categories. In 1880, Faulds advocated the use of fingerprints to identify criminals in Nature magazine. In 1891, Galton proposed the famous Galton classification system. After that, police departments in the United Kingdom, the United States, Germany, etc. successively adopted fingerprint identification as the main method of identification. With the development of computers and information technology, the FBI and the Paris Police Department in France began to research and develop the Automatic Fingerprint Identification System (AFIS) in the 1960s for criminal case detection. At present, automatic fingerprint identification systems have been widely adopted by police stations around the world. In the 1990s, automatic fingerprint identification systems for personal identification were developed and applied. The fingerprint recognition system is a typical pattern recognition system, including fingerprint image acquisition, processing, feature extraction and comparison modules. Fingerprint image acquisition: Living fingerprint images can be collected through a specialized fingerprint collector. At present, fingerprint collectors mainly include in vivo optical, capacitive and pressure-sensitive types. For technical indicators such as resolution and collection area, the public security industry has formed international and domestic standards, but there is still a lack of unified standards for others. According to the collection area, fingerprints can be roughly divided into rolling fingerprints and flat fingerprints. Rolling fingerprints are commonly used in the public security industry. In addition, fingerprint images can also be obtained through scanners, digital cameras, etc. Fingerprint image compression: Large-capacity fingerprint databases must be compressed and stored to reduce storage space. The main methods include JPEG, WSQ, EZW, etc. Fingerprint image processing: including fingerprint area detection, image quality judgment, pattern and frequency estimation, image enhancement, fingerprint image binarization and refinement, etc. Fingerprint classification: Pattern type is the basic classification of fingerprints, which is divided according to the basic shape of the central pattern and triangle. The pattern is subordinate to the type and is named after the shape of the center line. my country's ten-fingerprint analysis method divides fingerprints into three major types and nine forms. Generally, the fingerprint automatic identification system divides fingerprints into bow-shaped patterns (arc-shaped patterns, tent-shaped patterns), dustbin-shaped patterns (left dustpan, right dustpan), bucket-shaped patterns, and mixed-shaped patterns. Fingerprint morphology and detailed feature extraction: Fingerprint morphological features include center (upper, lower) and triangular points (left, right), etc. The detailed feature points of fingerprints mainly include the starting point, end point, junction point and bifurcation point of the lines. Fingerprint comparison: Rough matching can be carried out based on the pattern shape of the fingerprint, and then the fingerprint morphology and detailed features can be used for precise matching to give a similarity score between the two fingerprints. Depending on the application, the similarity scores of the fingerprints are sorted or a judgment result is given as to whether they are the same fingerprint. Today's computer applications, including many very confidential file protections, mostly use the user ID + password method for user identity authentication and access control. However, if the password is forgotten or stolen by others, the security of the computer system and files will be threatened. With the advancement of technology, fingerprint recognition technology has slowly begun to enter the computer world. At present, many companies and research institutions have made great breakthroughs in the field of fingerprint recognition technology, and launched many application products that perfectly combine fingerprint recognition with traditional IT technology. These products have been recognized by more and more users. Fingerprint recognition technology is mostly used in business fields with relatively high security requirements. Internationally renowned brands such as Fujitsu, Samsung and IBM, which have made great achievements in the field of business mobile office, all have fingerprint recognition systems with relatively mature technology and applications. The following is a review of fingerprint recognition. The application of the system in notebook computers is briefly introduced. As we all know, some brands of notebooks used fingerprint recognition technology for user identification two years ago. However, the fingerprint system launched at that time was an optical recognition system. According to current statements, it should belong to the first generation of fingerprint recognition technology. .

Since light cannot penetrate the surface of the skin (dead skin layer), the optical fingerprint recognition system can only scan the surface of the finger skin, or scan the dead skin layer, but cannot penetrate deep into the dermis. In this case, the cleanliness of the finger surface directly affects the recognition effect. If there is a lot of dust on the user's fingers, recognition errors may occur. Moreover, if people make a fingerprint hand model according to their fingers, it may also pass the recognition system, which is not very safe and stable for users to use. Today, notebook computers from leading international brands such as Fujitsu and IBM have begun to adopt second-generation fingerprint identification systems, changing the shortcomings of previous fingerprint identifications that were error-prone and unstable. The new generation of fingerprint systems uses capacitive sensor technology and uses small-signal semiconductor devices to create mountain-like fingerprint images. The capacitive sensor of the fingerprint reader emits an electronic signal, which will pass through the surface and dead skin layer of the finger, and reach the living layer (dermis layer) of the finger skin, directly reading the fingerprint pattern, thereby greatly improving the security of the system. .