FRR stands for False Rejection Rate, which is a term commonly used in the field of biometrics and security systems. It refers to the probability that a genuine user will be incorrectly rejected or denied access by the system. The False Rejection Rate is a measure of how often the system fails to recognize the legitimate user, causing inconvenience and frustration.
In biometric authentication systems like fingerprint or facial recognition, the FRR is a critical metric that evaluates the system's accuracy and reliability. A lower FRR implies that the system is more trustworthy as it correctly recognizes and grants access to legitimate users.
The FRR is determined by calculating the ratio of the number of false rejections to the total number of attempted authentications. It is usually expressed as a percentage. For example, if a system falsely rejects 5 out of every 100 legitimate users, the FRR would be 5%.
Minimizing the FRR is crucial for ensuring user satisfaction and preventing unauthorized access. However, reducing the FRR often involves a trade-off with the False Acceptance Rate (FAR), which measures the probability of incorrectly accepting an imposter. Striking a balance between the two rates is crucial in achieving optimal system performance.
In summary, the False Rejection Rate (FRR) is a measure of how often a biometric or security system fails to correctly recognize a genuine user, leading to their denial of access. It plays an important role in evaluating the accuracy and reliability of such systems.
