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


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.


Instructions coming soon. We anticipate participation beginning in Fall 2024. Please review, comment on, and study the Application Programming Interface (API) and test plan while you wait.


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


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

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Created June 21, 2024