Currently there are many methods of biometric identification: fingerprint, eye iris, retina, voice, face etc. Each of these methods has certain advantages and disadvantages, which must be considered in biometrical system developing: system reliability, price, flexibility, necessity of physical contact with scanning device and many others. Selecting the certain biometrical identification method or using the multi-biometrical system can help to support these, often discrepant, requirements.
Face identification can be an important alternative for selecting and developing optimal biometrical system. Its advantage is that it does not require physical contact with image capture device (camera). Face identification system does not require any advanced hardware, it can be used with existing image capture devices (web cams, security cameras etc.).
Face is not so unique as fingerprints and eye iris, so its recognition reliability is slightly lower. However, it is still suitable for many applications, taking into account its convenience for user. It can also be used together with fingerprint identification or another biometrical method for developing more security critical applications.
Overview
FingerCell Embedded Development Kit (EDK) is based on the FingerCell embedded fingerprint recognition algorithm that is especially designed to be used in embedded low-power and comparably low-CPU-power applications. FingerCell EDK includes libraries for various operating systems and embedded platforms (i.e. ARM or ARCA), as well as drivers for embedded sensors and source codes for sample applications.
Customers who want to use another platform can obtain the FingerCell ANSI C source code package and port the software to the required platform.
Embedded hardware development could be completely avoided by obtaining FingerCell 2.0 Device EDK, which already includes a ready-to-use stand-alone fingerprint identification device with integrated an U.are.U 4000 sensor.
The following types of FingerCell 2.0 EDK are available:
- FingerCell 2.0 Device EDK - a kit for fast development of an embedded system. Includes a ready-to-use FingerCell embedded device (hardware) with the FingerCell algorithm and demo software installed, drivers for image input from fingerprint sensors, programming samples and documentation. After developing an application with FingerCell Device EDK, customers can obtain additional hardware units for commercialization of the developed product.
- FingerCell 2.0 Library EDK - is intended for biometric system projects using hardware based on ARM processors. Includes FingerCell library, programming samples and documentation for Windows CE and Linux.
- FingerCell 2.0 source code EDK - is intended for large biometric system projects using third party or custom hardware. Includes FingerCell source code, samples and documentation for MS Windows CE and Linux.
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FingerCell 2.0 Device EDK is designed for fast development of a stand-alone access and attendance control system. The kit includes a ready-to-use fingerprint identification device with DigitalPersona U.are.U 4000B sensor module, CPU, LCD display, keypad and ports for network connection, thus no additional hardware development is required. The whole system uses Linux and includes software for integrating FingerCell technology to this device to create a fast and accurate fingerprint identification solution.
- One FingerCell Device with FingerCell algorithm installed
- One FingerCell 2.0 installation license for the algorithm installed in the
included FingerCell Device
- DigitalPersona U.are.U 4000 sensor driver for ARCA Linux platform
- Linux user-space drivers for image input from Tacoma CMOS, Startek FM200, AuthenTec AF-S2, AuthenTec AES4000 and Fujitsu MBF200 fingerprint sensors via USB port on FingerCell Device
- Sample applications (see below)
- Documentation
- 350 MHz ARCA CPU
- 16 MB SDRAM
- 4MB NOR Flash
- 128*64 LED display
- Keypad
- Ethernet 10M/100M
- Double-line Standard USB 1.1
- AC97 Codec
- Serial communication: RS232, RS485
- DigitalPersona U.are.U 4000B Fingerprint sensor
- RS232 Serial communication cable
- 5V DC power adapter
Software specifications (installed on device):
- FingerCell algorithm
- Redboot boot loader with tftp support
- Linux kernel with nfs support and DigitalPersona U.are.U module
- BusyBox with telnet server and tftp client
FingerCell 2.0 Device EDK includes three sample applications with source codes. These applications were designed to demonstrate possible usage scenarios of the FingerCell device:
- Stand-alone sample application
This sample application demonstrates how the FingerCell device can be used as a stand-alone identification system. Fingerprint enrollment, identification and verification are performed on the device, and fingerprint templates are stored into a file on the device. Sample source code demonstrates how to use the device's LCD, numpad, embedded fingerprint sensor and LEDs.
This sample shows the menu with available operations on the device's LCD display. The user can chose a menu command by pressing a number key on the device's numpad. Possible commands are Enrollment (with or without generalization), Identification and Verification. The user can also clear the database that stores fingerprint templates.
During enrollment the user is asked to put a finger on the scanner. After scanning the finger a PIN code must be entered. During enrollment with generalization, 3 fingerprints are scanned and generalization is performed to produce a fingerprint template of higher quality. During identification, the fingerprint template is matched against the templates present in the database. Identification results are shown on the device's screen. During verification the identity of the user must be confirmed with a PIN code.
- Simple network sample application
This sample application demonstrates simple communication between FingerCell and a PC. The sample is based on the first sample. The only difference is that every operation performed on the device is logged and sent to the PC via a network.
- Advanced network sample application
Note, that this sample could be run only by VeriFinger SDK customers, as the VeriFinger installation license is required on the PC side.
The sample shows how to perform identification and verification on a PC. The user interface of the device application is very similar to the first sample: the user must choose an operation from the menu. After scanning a fingerprint, the fingerprint's features are extracted on the device using the FingerCell algorithm, but the template is sent to the PC for enrollment, identification or verification using the VeriFinger algorithm. After the PC performs the requested operation, the results are sent back to the device and are shown on the LCD display.
FingerCell 2.0 Library EDK includes the FingerCell 2.0 library for developing custom products. The developed product can run on ARM-based platform under Linux or Microsoft Windows CE.
FingerCell 2.0 Library EDK contains the following components:
- MS Windows CE components:
- FingerCell 2.0 library (for Microsoft Visual Studio 2005 with SP1)
- Source code of FingerCell library usage sample application in Visual C++ 2005 SP1
- ARM Linux components:
- FingerCell 2.0 library (for Arm-Linux GCC C compiler)
- Source code of sample embedded application in ANSI C (project for Arm-Linux GCC C compiler)
- User-space drivers for image input from Tacoma CMOS, Startek FM200, AuthenTec AF-S2, AuthenTec AES4000 and Fujitsu MBF200 fingerprint sensors via USB port
- FingerCell 2.0 EDK documentation.
- ARM-based processor with at least 200 MHz CPU clock rate for fingerprint enrollment in less than one second (supported ARM processor core families are: ARM9, ARM10, ARM11, StrongArm, XScale).
- At least 512 Kb of memory for FingerCell code and data arrays (the recommended amount could be different, as it depends on fingerprint image size)
- Fingerprint sensor, which has the driver available for integrator
- ARM Linux (glibc 2.3.4 or later) or Microsoft Windows Mobile 2003 (or later) operating system
Neurotechnologija also offers FingerCell 2.0 EDK on a 30 day trial. The downloadable trial kit allows developers to explore the EDK's possibilities and to try it in real environments and real applications. FingerCell EDK includes samples for iPAQ Pocket PC h5500 and iPAQ Pocket PC hx2700 series devices with integrated fingerprint sensors.
Note: FingerCell 2.0 EDK trial requires constant Internet connection during evaluation.
FingerCell 2.0 source code EDK is intended for developers who are going to integrate fingerprint identification technology into a custom embedded device.
FingerCell 2.0 source code EDK contains the following components:
- 10,000 FingerCell 2.0 installation licenses
- FingerCell 2.0 source code:
- Project for GCC compiler (ARM-Linux platform)
- Project for MS Visual Studio 2005 (Pocket PC 2003 platform)
- FingerCell 2.0 Algorithm and Source Code Description
- Sample applications:
- Project for GCC compiler (ARM-Linux platform)
- Project for MS Visual Studio 2005 (Pocket PC 2003 platform)
- Linux user-space drivers' source codes for Tacoma CMOS, Startek FM200, AuthenTec AF-S2, AuthenTec AES4000 and Fujitsu MBF200 fingerprint sensors connected via USB port
- FingerCell 2.0 EDK developers' guide
- ARM based processor with at least 200 MHz CPU clock rate for fingerprint enrollment in less than one second (supported ARM processor core families are: ARM9, ARM10, ARM11, StrongArm, XScale).
- At least 512 Kb of memory for FingerCell code and data arrays (the recommended amount could be different, as it depends on fingerprint image size)
- Fingerprint sensor, which has the driver available for integrator
- ARM Linux (glibc 2.3.4 or later) or Microsoft Windows Mobile 2003 (or later) operating system
Please note that FingerCell 2.0 Source Code EDK could be easily ported to most other platforms and processors.
Neurotechnologija offers Template Management and Conversion Add-on - a product for template standards support integration for systems based on VeriFinger SDK or FingerCell EDK. |
