Informatique

Hybrid Fingerprint Recognition Embedded Module

The Digimore FPM-8530G3 is one chip fingerprint reader designed for integration into products with USB 2.0 full speed interface. It configures as USB mass storage device so it no need additional effort to handle driver.

The reader within the ST STM32F446 device is high performance, low power consumption 32-bit microcontroller based around an ARM Cortex-M4 processor core and the fingerprint algorithm is processed on it.

The Fingerprint sensor module can be used under 2.0mm cover glass. The fingerprint sensor uses unique patented technology. In the 2.0mm cover glass, it has a good image quality. The sensor interface is SPI and internal touch function to wake up the host.

Furthermore, the high quality hybrid sensor has sufficient effective area. The active area allows stable imaging and ability to cope with mass market applications in need of both security and convenience.

SPECIFICATION
CPU : ARM Cortex M4 Core (ST STM32F446)
Sensor : Ultra-thin hybrid sensor
Effective Area of the Sensor : 6 x 6 (mm)
Resolution/ Image Size : 508 dpi; 120 x 120 pixels
Number of fingerprints : Support up to 100 fingerprints
Algorithm Matching Mode : 1 : 1, 1 : N
Size of Template : 32kb
Communication Interface : USB 2.0, UART default baud rate=115200bps after power on
FAR/FRR : False Acceptance Rate (FAR) 1/100K; False Rejection Rate (FRR) < 5%
Enrollment Time : <8 sec. (8 fingerprints)<br /> Identification Time : <0.8 sec (30 fingerprints); <1.2 sec (50 fingerprints); <2 sec (100 fingerprints)<br /> Operating Voltage/Current : 3.3V + 5% ; Typical 130mA
Operating Temperature : -20 to 60 degrees Celsius (20% to 80% RH, 25 degree Celsius)
Storage Temperature : -20 to 80 degrees Celsius (10% to 80% RH, 25 degree Celsius)
SDK Demo Support : Logical design also available upon requested

Localisation : 10 Fl., No. 61, Yan-Ping S. Rd., 100 Taipei,
Personne à contacter : Sam Yeh, 886 2 2311 3299

Bonne affaire : acheter au vendeur

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Hybrid Fingerprint Recognition Embedded Module

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embedded, module, recognition, fingerprint, hybrid
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