Synel Biometric Technology
by Synel Industries

What is Biometrics Technology?

Biometrics technology is an irrefutable verification or identification of a person by various physiological characteristics, which cannot be transferred or copied. Synel uses Bioscript's sensor and controller as an OEM. Synel has implemented the module in two main products: Synel Sy-780 for Time & Attendance and PrintX for Access Control.

Biometric Authentication
Biometric authentication measures the unique, invariable biological characteristics of an individual. One of the most common biometrics used today is fingerprint information.
 
The biometric information is captured during enrollment and translated into a template, which is stored for subsequent authentication. The template is then stored in the database or on the server. During authentication, the biometric information is captured and compared against the stored template. If the user is valid, the two images will match, and authentication is achieved.

Pattern Recognition
Synel uses a pattern recognition algorithm as the basis for its fingerprint authentication systems. This algorithm processes the entire fingerprint image, rather than simply selecting a limited number of minutiae points. This means that pattern recognition algorithms are more robust as they are not significantly affected by the loss of information when a finger is scarred, damaged, or dirty.

Protecting your rights!!
The integrity of the finger print template is guaranteed. We do not keep an image of your fingerprint!!! Our Biometric solution scans the fingertip ridges at a very low resolution, and translates the scan through an algorithm to a number. Only that number is stored.
 
How does it work?
Every time a Fingerprint is presented to the sensor, it will be compared to the appropriate algorithm in the database.

Finger Print Verification - is the process of entering a pin # or using a card and comparing the current scanned image against a stored template. Response time is 1 sec

Finger Print Identification - using the finger template for comparison. No need to enter a number or use a card. Response time 2-3 seconds.

Bioscrypt - Algorithm
Bioscrypt uses pattern recognition as the basis for its fingerprint authentication algorithms. The algorithm is a set of mathematical routines by which a fingerprint image is captured, filtered, stored and, later, matched. The template that is stored is a representation of these mathematical routines rather that the fingerprint image itself. The template is proprietary and unlike minutia-based systems the template is not compatible and therefore cannot be used in conjunction with government identity or police programs. While our biometric template is proprietary, the algorithm is uniquely positioned to provide an open interoperable platform for fingerprint capture devices. An original enrollment captured on an AuthenTec sensor (for example) is always maintained and employable in the event that verification is required on a sensor made by another leading provider like Polaroid, Infineon-Siemens, Veridicom or ST MicroElectronics.

Data "rich" technology
Traditional minutia technology relies on unique reference points (minutia) on the finger. For a given finger the number of minutia is limited. The Ridge Recognition algorithm, in contrast, is unique in its ability to record and match the ridge pattern of the finger. For a given area of fingerprint, the ridge pattern provides substantially more data than minutia alone, resulting in the following advantages:

• Higher overall accuracy - more data points allow more precise matching.
• Higher tolerance for distortions - factors such as cuts and swelling have a much smaller impact on the verification process.
• Ability to effectively use smaller sensors - the surface area of the sensor can be significantly reduced while high accuracy is maintained.

As a result of Ridge Recognition's innovative approach, the algorithm has achieved an average error rate of .1 % or 1 in 1000, while the best minutia algorithms are believed to achieve approximately 1% or 1 in 100. An error occurs when an unauthorized user is falsely authorized ("false acceptance"), or when an authorized user is falsely rejected ("false rejection"). In external tests performed by AuthenTec, a fingerprint sensor manufacturer, Bioscrypts's Ridge Recognition resulted in an impressive .01 % false acceptance rate or 1 in 10,000 and .1 % false rejection rate or 1 in 1,000.
 
Traditionally, one of the biggest drawbacks of fingerprint identification and authentication has been the distortion of the fingerprint image by factors such as cuts and swelling. Ridge Recognition solves this problem by precisely measuring distortion and removing it from the ridge pattern. This technique is not possible with minutia algorithms because the gaps between minutia do not allow accurate estimation of the distortion. In addition, Ridge Recognition functions with smaller-sized sensors. A continuing goal in biometrics is to minimize sensor size. Given the high costs of silicon, smaller sensors allow for significant cost reduction. Also, smaller sensors enable more feasible implementation in products where space for a sensor is limited. The drawback to smaller fingerprint sensors has traditionally been that they capture fewer data points, thus limiting accuracy and security. Ridge Recognition, however, does not have this drawback because of its data rich imaging approach.