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NIST-Proven Accuracy

NEC’s unsurpassed face and fingerprint matching algorithm provides high accuracy and selectivity regardless of the database size and image 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), the results have validated NEC AFIS as the best in the industry.

Working with NEC means having access to decades of biometrics expertise and proven biometrics technologies that ensure performance, accuracy and reliability.

Face Recognition

Fingerprint Recognition

Note: NIST test results do not constitute endorsement of any particular system by the government. For more information, visit www.nist.gov.

In FpVTE2012, which, unlike FpVTE2003, was intended to evaluate on operational datasets of an unprecedentedly large scale to reflect real-world applications, NEC AFIS achieved the highest one-to-many identification accuracy, thereby proving its feasibility and superiority.

NEC face recognition technologies were ranked No. 1 in the MBE Still-Face Track in 2010 carried out by the National Institute of Standards and Technology (NIST), commissioned by the Department of Homeland Security. MBE's Still-Face Track benchmark test employed accuracy evaluation tests with a dataset of over one million face images, which were collected from actual criminal databases and face images used for visa applications. NEC engines are shown as Vxx in the following figures.

Highest identification rate

Highest 95% identification rate from 1.8 million visa applicants.

Lowest False Reject Rate 0.3% in processing the civil database at False Accept Rate of 0.1%.

Highest 92% identification rate from a 1.6 million person criminals.

Lowest False Reject Rate 4% in processing the criminal database at False Accept Rate of 0.1%.

Lowest verification error rate

Widest acceptance performance against yaw-angle variation.

Most robust against time-elapsed between photographs.

Most robust against short inner-eye distance.

Most robust against high compression rate (JPEG, inner-eye distance=96 pixels).

Most robust against high compression rate (JPEG2000, inner-eye distance=96 pixels).

Highest query processing speed by using 16 cores parallelly.

(1.6 million images can be processed in approx. 0.4 second)

For more information, please refer to NISTIR 7709 and NISTIR 7830.

NEC face recognition technologies were ranked No. 1 in the MBGC "Still-Face" Challenge Problem in 2009, carried out by the National Institute of Standards and Technology (NIST), commissioned by the Department of Homeland Security.

The facial images evaluated in the Still-Face Challenge Problem were taken by high resolution digital cameras under a variety of challenging conditions, including compressed images used for IC passports, and images taken under poor indoor lighting or direct sunlight. These situations were designed based on anticipated real-world scenarios.

At this test, NEC's superior test results have demonstrated highly accurate performance. Its False Reject Rate of 2.1% and False Accept Rate of 0.1% for outperformed technologies competing in the same category.

Highest verification rate

High tolerance to variations in illumination and compression

Lowest false reject/accept rate

0.3% False Reject Rate in processing visa application database
0.1% False Accept Rate in processing visa application database

For more information, please refer to NIST MBGC Still Face PROBLEM V2 FINAL PRESENTATION.

NEC's latent fingerprint matching technology was ranked number one in the world on the Evaluation of Latent Fingerprints Technologies (ELFT) test carried out by the National Institute of Standards and Technology (NIST), commissioned by the U.S Department of Homeland Security.

Among the world's leading fingerprint matching system vendors participating in this evaluation, NEC far surpassed even the second ranking vendor and reassured the superior position of NEC's fingerprint technology. NEC's high accuracy rate is achieved by the integration of improved matching technologies, such as a low-confidence minutiae adaptive matching algorithm, a zone matching algorithm, and recently developed image processing technologies specialized for latent fingerprints, such as a latent background noise removal algorithm and a low-quality fingerprint ridge recognition algorithm.

ELFT07 Phase2 - An Evaluation of Automated Latent Fingerprint Identification Technologies

The ELFT07 was a test of accuracy for searching latent fingerprints when using automatic feature extraction and matching, conducted in the United States in 2007 under the control of one of the US’s most respected government authorities, the NIST.

For more information, please refer to ELFT07 Phase2 - An Evaluation of Fingerprint Technologies 2007.

For more information, please refer to NIST Proprietary Fingerprint Template (PFT) Testing.

The growing use of biometrics for security applications in immigration and border control has focused attention on the importance of interoperability among multiple matching systems. The MINEX, conducted by NIST and sponsored by the Justice Management Division of the U.S. Department of Justice and the Department of Homeland Security US-VISIT program, determines the feasibility of using minutiae data for the exchange of fingerprint information between dissimilar fingerprint matching systems.

In MINEX04, NEC AFIS was evaluated as one of the most accurate algorithms in the minutiae data exchange interoperability test. Where vendors own proprietary minutiae data was used, NEC AFIS earned the top ranking (i.e., proved overall superiority).

For more information, please refer to MINEX04 - Minutiae Interoperability Exchange Test 2004.

In SlapSeg04, NEC AFIS achieved the top score in segmentation accuracy. Additionally, NEC AFIS proved most accurate in hand and finger position identification.

Slap fingerprints (or slaps) are plain four-finger images taken by pressing the four fingers of one hand onto a scanner or fingerprint card simultaneously. Slap segmentation is the process by which a single image containing four fingerprint images is divided into four images of the individual fingers. The high accuracy of slap segmentation contributes to the total system cost performance.

SlapSeg04 - Slap Fingerprint Segmentation Evaluation 2004

The SlapSeg04 was conducted by the NIST in collaboration with the U.S. Visitor and Immigrant Status Indicator Technology (VISIT) Program Office, the U.S. Department of Homeland Security (DHS) and the Federal Bureau of Investigation (FBI). This evaluation determined the accuracy of the slap fingerprint segmentation algorithm (i.e., one component of AFIS) used to segment slap fingerprint images into individual fingerprint images.

For more information, please refer to SlapSeg04 - Slap Fingerprint Segmentation Evaluation 2004.

In FpVTE2003, NEC AFIS earned the top ranking for its unparalleled matching accuracy in all accuracy tests using real data sets. To be particularly noted is that, even when the data had poor quality, NEC AFIS showed remarkable performance standing out from all competitor AFIS systems by a substantial margin.

FpVTE2003 - Fingerprint Vendor Technology Evaluation 2003

The FpVTE2003 was an international benchmark test of fingerprint matching, identification, and verification systems, conducted in the United States in 2003 under the control of one of the US’s most respected government authorities, the NIST.

For more information, please refer to FpVTE2003 - Fingerprint Vendor Technology Evaluation 2003.


Biometrics


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