Biometrics is an identification technology that relies on the physical characteristics of the human body for identity verification. There are three main types of biometrics technology, namely face recognition, iris recognition, and fingerprint recognition. From the perspective of the technological development stage, the current fingerprint recognition technology has been very mature, and the biometric fingerprint terminal has a higher recognition rate after the update iteration, and the cost performance is very high, so its application value has been recognized by many parties.
The current mainstream fingerprint recognition algorithm is based on detailed features such as the end points and bifurcation points of fingerprint lines. With the application of fingerprint recognition technology in mobile devices, the size of fingerprint collection chips has become increasingly miniaturized, and recognition algorithms based on three-level features such as sweat holes and line shapes have received increasing attention.
When the finger presses the screen, the OLED screen emits light to illuminate the finger area, and the reflected light illuminating the fingerprint returns to the sensor close to the bottom of the screen through the gap of the screen pixels. The acquired fingerprint image is compared with the image entered by the mobile phone for the first time, and finally the identification judgment is made.
Since LCD screens cannot self-illuminate, products that currently support fingerprint recognition under optical screens generally use OLED screens. Moreover, the self-luminous, bendable, and thin-thickness characteristics of OLED screens are strong support for fingerprint recognition technology under optical screens. Fingerprint recognition under the optical screen can effectively avoid the interference of ambient light, and has better stability in complex environments.
EKEMP's H5 biometric fingerprint terminal integrates suprema's FAP20 certified optical fingerprint scanner for user registration and identity authentication. It provides advanced machine-learning based Live Finger Detection technology that distinguishes fake fingerprints made from various materials including clay, rubber, silicon, glue, paper, film and more. It also can get normal fingerprints even under 100,000 LUX direct light, which is equivalent to direct sunlight.