 |
| Quantity: | |
|---|---|
HFP-360
HCCTG
HFP-360 module can communicate with the master device through two communication protocols, USB and UART. As a slave device, this module is controlled by the master device by sending relevant commands. The main device is connected to the module through a 4PIN * 1.25 electronic cable.
When reading fingerprint images, it has a sensitive response and judgment to both dry and wet fingers, achieving the best imaging quality and suitable for a wide range of people.You can also customize self-learning and adaptive functions to automatically adjust parameters based on user habits, climate change, and other changes, achieving better matching. Equipped with self-learning function, in the fingerprint recognition process, new fingerprint feature values are successfully extracted and recognized, and then fused into previous fingerprint features.
Specification
Size | 30(L)*22(W)*1.1(H) mm | |
Sensor | Window size | 18*12 mm |
Pixels | 256*360 pixels | |
Resolution | 508 DPI | |
Backlight color | None | |
Algorithm | Overall recognition time | <1(s)
|
Search time | <0.5(s) | |
Storage capacity
| 1000(pcs) (supports local and backend storage) | |
False admission rate | <0.001% | |
Authenticity | <1% | |
Interface | UART | Baud rate bps:57600 Data bit:8 Stop bit:2 Check bit:None |
USB | 2.0FS | |
Electrical parameters | Voltage | 3.0-3.6(V),Standard:3.3V |
Standby current
| 5(uA);<40 mA(Only sensing part works) | |
Working current | <200 mA | |
Work environment | Temperature | -20 ℃~60 ℃ |
Humidity | 40％ ℃~80％ ℃(No condensation) | |
HFP-360 module can communicate with the master device through two communication protocols, USB and UART. As a slave device, this module is controlled by the master device by sending relevant commands. The main device is connected to the module through a 4PIN * 1.25 electronic cable.
When reading fingerprint images, it has a sensitive response and judgment to both dry and wet fingers, achieving the best imaging quality and suitable for a wide range of people.You can also customize self-learning and adaptive functions to automatically adjust parameters based on user habits, climate change, and other changes, achieving better matching. Equipped with self-learning function, in the fingerprint recognition process, new fingerprint feature values are successfully extracted and recognized, and then fused into previous fingerprint features.
Specification
Size | 30(L)*22(W)*1.1(H) mm | |
Sensor | Window size | 18*12 mm |
Pixels | 256*360 pixels | |
Resolution | 508 DPI | |
Backlight color | None | |
Algorithm | Overall recognition time | <1(s)
|
Search time | <0.5(s) | |
Storage capacity
| 1000(pcs) (supports local and backend storage) | |
False admission rate | <0.001% | |
Authenticity | <1% | |
Interface | UART | Baud rate bps:57600 Data bit:8 Stop bit:2 Check bit:None |
USB | 2.0FS | |
Electrical parameters | Voltage | 3.0-3.6(V),Standard:3.3V |
Standby current
| 5(uA);<40 mA(Only sensing part works) | |
Working current | <200 mA | |
Work environment | Temperature | -20 ℃~60 ℃ |
Humidity | 40％ ℃~80％ ℃(No condensation) | |
