FRIF TE Exemplar One-to-Many (FRIF TE E1N)

Test Results (coming soon) | Mailing List | Test Plan (PDF) and API

About

Friction Ridge Image and Features (FRIF) Technology Evaluation (TE) Exemplar One-to-Many (E1N), or FRIF TE E1N, is an open-set identification evaluation of algorithms that automatically extract and use features from all types of exemplar friction ridge images (e.g., rolled fingerprints, palm prints, slaps) and later use those features to search for similar candidates in databases of millions of subjects. E1N exercises the template creation and template search algorithms at the core of an Automated Biometric Identification System (ABIS), not the system itself.

Participate

1. Fill out the request for the dataset agreement to receive the validation dataset.
2. Wrap your algorithm in the FRIF TE E1N application programming interface (API) and build it as a shared library.
3. Follow the instructions for validation on GitHub.
4. Complete, sign, date, and scan the participation agreement.
5. Upload the signed and encrypted output of validation (step 3), your public key, and your completed and signed evaluation agreement via the NIST FRIF TE E1N submission form.

History

FRIF E1N is a relaunch of previous evaluations conducted by NIST under the FpVTE moniker. 

• FpVTE 2012
  • NIST IR 8034: Fingerprint Vendor Technology Evaluation (Jan 2015)
• FpVTE 2003
  • NIST IR 7123: Fingerprint Vendor Technology Evaluation 2003: Summary of Results and Analysis Report (June 2004)

Contact

Questions and comments should be addressed to the team privately by emailing frifte [at] nist.gov (frifte[at]nist[dot]gov). Public comments on code can be made on the FRIF TE GitHub Issues Page.

frifte+subscribe [at] list.nist.gov (Subscribe to our email list) to receive a low-volume stream of updates or browse the archives.