FingerCell SDK
Fingerprint identification for embedded platforms
FingerCell technology is designed for embedded biometric systems developers and features compact, sensor-independent and cross-platform fingerprint recognition algorithm. It offers decent performance on various embedded devices based on low-power microcontrollers or processors.
FingerCell is available for integrators as Software Development Kits (SDK) with FingerCell library or source code for developing a fast and reliable system on embedded or mobile platform.
Technical Specifications
385 ppi is the minimal recommended fingerprint image resolution for FingerCell template extraction algorithm.
If the system needs to perform person's identification (1-to-many matching), all fingerprint templates should be loaded into RAM, thus the maximum fingerprint templates database size is limited by the amount of available RAM. See system requirements for more information about the required amounts of RAM and flash storage.
The performance specifications below are provided for embedded hardware based on ARM Cortex-M4F microcontroller, running at 168 MHz clock rate. The specifications are provided for fingerprint templates without sub-records and change proportionally for templates with sub-records.
| FingerCell 3.3 algorithm technical specifications | |
|---|---|
| Template extraction time (milliseconds) (1) | 650 |
| Template verification time (milliseconds) (2) | 4 |
| Template identification speed (templates per second) (2) | 250 |
| Template size with 16 minutiae (bytes) (3) | 152 |
| Template size with 64 minutiae (bytes) (3) | 488 |
- For performing the operation with 180 x 256 pixels fingerprint images at 385 ppi resolution, or, correspondingly, 234 x 332 pixels at 500 ppi.
- For templates containing up to 64 minutiae.
- The template size depends on the actual number of minutiae stored in it. The provided values are reference sizes for the corresponding numbers of minutiae.
