Oops! It appears that you have disabled your Javascript. In order for you to see this page as it is meant to appear, we ask that you please re-enable your Javascript!
ARDIoT | Internet of Things & Smart Cities

Finger Print Authentification

Let You're Biometric be your Identity!

The most efficient and accurate authorization has been dedicated fingerprint identification by the leading technology over three decades. And today fingerprint biometrics is one of the advanced solution for both enforcement and identity management applications.

Fingerprint identification technology is empowered by a unique matching algorithm (i.e., the minutiae and relation method) that uses ridge counts and the relationship between minutiae. This enables us to provide the lowest false accept and false reject rates (FAR and FRR) – with the fastest 1:n database searches for identification.

In addition, Positive Identification (PID) adds another innovative and competitive edge to thr fingerprint identification technology. Emerging from AFIS technology, PID provides the most advanced pattern identification and fingerprint matching available today.

AFIS Solution


AFIS delivers high-level benefits and offers a variety of advanced features to meet law enforcement identification demands.

  • Fingerprint and palmprint identification
  • Positive Identification (PID)
  • Advanced processing for finger, latent, palm and slap matching
  • Enhanced Search Sending to Other AFIS
  • Seamless interface to live scan units, mugshot systems, criminal history systems, etc.

The superiority of AFIS matching cannot be overstated. AFIS does not just match fingerprints to solve crimes. Unlike AFIS is not only a tenprint registration system but also a fingerprint repository for the identification of dangerous criminals. Furthermore, the capability that distinguishes AFIS technology from the other solutions, is that its unsurpassed latent identification accuracy and speed – solving crimes is the number one AFIS priority.

AFIS is the first solution that uses ridge counts and relationships between minutiae in its matching algorithm. This algorithm allows AFIS to match distorted prints while maintaining matching selectivity. In addition, NEC’s use of “zone” data reduces the number of false minutiae by ensuring that only minutiae in “clear zone” are used in matching. These features allow customers to achieve high hit rates while reducing the number of candidates to be compared with.

A finger minutia is a fingerprint ridge ending, or a ridge bifurcation where the ridge separates into two ridges – the characteristics that make each fingerprint unique. Because the skin at the ends of fingers, where fingerprint patterns are located is soft, the positions and directions of minutiae are subject to great deal of distortion, depending on how the finger is pressed against the surface receiving the print. The number of ridges between minutiae however, never changes. By encoding these ridge-counts together with the minutiae, that is the relation between minutiae, AFIS provides the most positive matching for all types of fingerprints.

The unsurpassed fingerprint matching algorithm provides high accuracy and selectivity regardless of the database size and print quality. Through a comprehensive range of tests, from small one-to-one verification all the way up to large-scale, high-volume identification matching, conducted by the National Institute of Standards and Technology (NIST).

NIST Proprietary Fingerprint Template (PFT) Testing

The PFT tests are conducted by NIST to evaluate fingerprint biometrics matching systems using vendor-supplied SDKs. These evaluations are ongoing and new SDKs can be included in the test at any time.

One-to-one fingerprint matching with Vendor SDK matchers test This test measures the 1:1 accuracy of fingerprint matching systems used for 1:1 verification.

Two finger matching with Vendor SDK matchers test As an extension of the 1:1 fingerprint matching tests, this test is designed to evaluate the matching accuracy that can be achieved by combining scores for the right and left index fingers. With the AFIS algorithms performance mirrored its performance in the 1:1 Fingerprint Matching Test.