Neurotechnologija Announces New FaceCell Facial Recognition Embedded Development Kit and FingerCell 2.0 for Embedded Fingerprint Recognition Systems
FaceCell and FingerCell Can Be Used Together to Create Embedded Multi-Biometrical Applications on a Variety of Systems and Compact Mobile Devices
Vilnius, Lithuania – January 10, 2007 – Neurotechnologija, a provider of high-precision biometric identification technologies, today announced the availability of two biometric embedded development kits (EDK): FaceCell, the company’s first EDK for development of facial recognition applications on embedded devices and FingerCell 2.0, a new version of their EDK for embedded fingerprint recognition. While developers can use either FaceCell or FingerCell independently, the two algorithms also have been developed to work seamlessly together using the same interface, enabling the creation of multi-biometrical embedded applications that run on a variety of systems and compact or mobile devices. Using both face and fingerprint recognition together provides a higher level of security and reliability and faster matching speeds, even when using very large databases.
FaceCell and FingerCell 2.0 are designed to be used in low cost, low power, compact and/or mobile embedded devices such as doors, entry gates, handheld PCs and cell phones; and they are compatible with Neurotechnologija’s recently announced VeriLook 3.0 facial recognition and VeriFinger 5.0 fingerprint recognition algorithms for easy integration in mixed PC-embedded systems. Both FaceCell and FingerCell 2.0 run on the Windows CE, Windows Mobile and ARM Linux operating systems, and source code is available for developers and integrators who wish to implement applications on other device platforms.
“We are very pleased to offer the new FaceCell EDK at the same time we are releasing FingerCell 2.0,” said Algimantas Malickas, CEO of Neurotechnologija. “Each of these products individually has tremendous potential for the development of embedded biometrical systems; and used together they allow even more possibilities for applications that require a higher degree of security or for situations when a second identification method is needed, such as access control for disabled people or for manual workers whose fingerprints may be difficult to scan.”
The FaceCell algorithm provides a high level of reliability with a fast matching speed of up to 3000 faces per second. It can be used in a wide range of applications and can be easily integrated into devices that have built-in video cameras, such as Pocket PCs and cell phones, without having to develop any special hardware.
Using facial recognition in embedded devices can be more practical in many situations and more comfortable for the user because he or she does not need physical contact with the device. For example, FaceCell can be used on hand-held devices as an alternative to a PIN code for device login or for security or data protection purposes when only the recognized user is allowed access. FaceCell can also be used in the field for person identification applications such as law enforcement or insurance. FaceCell EDK includes a fully functional programming sample for iPaq HW6915 and similar properties can be implemented for use on other devices. Face detection and template extraction takes 1-2 seconds, depending on frame size and processor speed (200 MHz – 400MHz or faster processors are recommended).
FingerCell 2.0 can match up to 700 fingerprints per second and can be used for both 1:1 matching and 1:many (1:N) identification in embedded applications for access control, time and attendance and device security, among others. Developed on the VeriFinger basis, the FingerCell 2.0 algorithm has been modified to achieve faster image processing and feature extraction when used in low-power/low CPU-power devices. FingerCell is fully tolerant to fingerprint translation and rotation and can recognize a fingerprint from a small portion of it. The FingerCell 2.0 algorithm provides enhanced reliability compared to FingerCell 1.2. When set to the same False Acceptance Rate (FAR), the False Rejection Rate for FingerCell 2.0 is 20% - 50% lower than the FingerCell 1.2 algorithm. FingerCell EDK includes samples for iPAQ Pocket PC h5500 and iPAQ Pocket PC hx2700 series devices with integrated fingerprint sensors.
Both FaceCell and FingerCell 2.0 are available now with highly competitive licensing options through Neurotechnologija or from distributors worldwide. For a list of distributors see http://www.neurotechnologija.com.
Neurotechnologija provides biometric fingerprint and face identification algorithms and software development products to security companies, system integrators and hardware manufacturers. More than 1000 system integrators and fingerprint sensor providers worldwide integrate Neurotechnologija’s technologies into their own products.
Drawing from years of academic research in the fields of neuroinformatics, image processing and pattern recognition, Neurotechnologija was founded in 1990 in Vilnius, Lithuania and released its first fingerprint identification system in 1991. Since that time Neurotechnologija has released more than 30 products and version upgrades for identification and verification of personal identity. For more information, visit: http://www.neurotechnologija.com.
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