Knowledge-base

FPIR measures how often a biometric system wrongly matches an unenrolled person to someone in the database, particularly in 1:N identification systems.

Automated Biometric identification Systems use human features for Biometric identification such as Facial recognition, IRIS scan, Liveness detection, and age verification.

Equal Error Rate (EER) is the point on ROC Curve where False Acceptance Rate (FAR) and False Rejection Rate (FRR) intersect and become equal.

Equal Error Rate (EER) is the point on ROC Curve where False Acceptance Rate (FAR) and False Rejection Rate (FRR) intersect and become equal.

The Receiver Operating Characteristic (ROC) curve is graph analyzing a binary classifier system showing trade-off between the True Positive Rate (TPR) and False Positive Rate (FPR).

False Non-Match Rate (FNMR) is the error rate in biometric identity verification tools that shows two identities belonging to the same person are flagged as a non-match.

False Match Rate (FMR) is the estimated error of a biometric authentication system in which it incorrectly matches two entirely different individuals and identifies them as the same person.

BPCER (Bona fide Presentation Classification Error Rate) is the false detection of a genuine user image as a fake one.

APCER in a biometric system is wrongly accepting a presentation attack as a genuine identification attempt.

FAR is the percentage error of a biometric identity verification system in accepting wrong identities.

False Rejection Rate is the frequency at which a biometric identity verification solution rejects a true identity.