Biometric Identification/Verification Brassboard Proof-of-Concept System Phase 2.

Abstract

DoD budget and personnel reductions drive requirements for an entry/access control system capable of non-intrusively identifying and verifying the identity of persons with a high degree of confidence and without a man in the decision loop. Operational Performance Requirements (OPR) were assembled from the SOW and Service requirements documents. An Iris-Based Biometric identification Verification Brassboard Proof-of-Concept System was designed and fabricated. The system was tested in accordance with the DNA-approved Test Plan and demonstrated at three sites. The test started with a data- base of 405 files and provided for enrollment of 160 added IrisCodes. Fifty verifications and 11944 identifications averaged 2.44 seconds each, with a False Accept Rate of 0. One hundred fifty impostor irises and 662 unenrolled irises were correctly rejected; one enrolled person wearing dirty glasses was incorrectly rejected, for a False Reject Rate of .05%. (The rejected enrollee was identified on second and all subsequent attempts, both with and without glasses.) Average enrollment time was 25 seconds, plus typing time. The system made 3,1001000 file comparisons without error. The system met or exceeded all test standards and requirements.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1995
Accession Number
ADA302620

Entities

People

  • Cletus B. Kuhla
  • Gerald O. Williams
  • James H. Lee
  • James T. Mchugh
  • John E. Siedlarz

Tags

Communities of Interest

  • Advanced Electronics
  • C4I
  • Energy and Power Technologies
  • Human Systems
  • Sensors

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Authentication
  • Biometric Security
  • Biometrics
  • Computational Science
  • Control Systems
  • Databases
  • Entry Control Systems
  • Eye
  • Gray Scale
  • Human Population
  • Identification
  • Identification Systems
  • Information Science
  • Medical Personnel
  • Pattern Recognition
  • Two Dimensional

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Sensor Fusion and Tracking Systems.
  • Software Engineering