CAMA-AFM31 capacitive biometric fingerprint sensor module for fingerprint scanner
Advantages
1. Module integrated with sensor as smallest appearance
2. Advanced Technology of self study function
3. Support 360 degree identifying
4. Better performance with dirty fingers, dry fingers, wet fingers
5. Excellant performance & fast identifying speed
Description
CAMA-AFM31 capacitive fingerprint sensor module is a fingerprint oem module for secondary development. It features small size, low power consumption, simple ports,high reliability, small fingerprint template (496bytes), large fingerprint capacity, etc. It is convenient to be embedded to user system for realizing clients required fingerprint verification products.
CAMA-AFM31 outstandingly features self-learning function. During the fingerprint verification process,the latest collected fingerprint features would be integrated into the fingerprint database automatically so that the users would obtain better and better fingerprint verification result.
Feactures
Live Scan Function (Avoid fake fingerprint)
2000 fingerprints
Auto-learning Function (Automatically updating the fingerprint features)
496 byte fingerprint template
Small size fingerprint sensor
500 DPI resolutions
Able to Set the Baud Rate and Equipment Number
Access to standby situation by instruction control module
Parameters
No.
Item
Description
1
Model
CAMA-AFM31
2
Sensor
FPC1020 Capacitive Fingerprint Sensor
3
Fingerprint image
242 * 266(pixel)
4
Resolution
500dpi
5
Power Supply
DC3.3V
6
Work current
<100mA, Standby Mode less than 5mA
7
Communication port
USB/UART
Specifications
Communication interface :USB/ UART
Optic sensor is reliable and Low-cost,High ESD Protection
1:N Identification (One-to-Many)
1:1 Verification (One-to-One)
High speed fingerprint identification algorithm engine
Self study function
Fingerprint template data read from /write to FLASH memory function
Get Feature Data of Captured fingerprint and Verify/IdentifyDownloaded Feature withCaptured fingerprint(Specially designed for fingerprint stored in IC card)
Identify Downloaded Feature with Captured fingerprint
