The Equal Error Rate (EER) is the best indicator of the accuracy of a biometric system. It is the point where both the False Acceptance Rate (FAR) and False Rejection Rate (FRR) are equal. The lower the EER, the better the system is considered to be because it means the biometric system makes fewer mistakes in both falsely accepting an imposter and falsely rejecting an authorized user.
The incorrect answers: While False Acceptance Rate (FAR) is an important metric for a biometric system, it only measures the likelihood of the system incorrectly accepting an access attempt by an unauthorized user. It does not take into account the system’s ability to correctly identify authorized users, which is why it is not the best overall indicator of accuracy.
Similar to FAR, the False Rejection Rate (FRR) only measures one aspect of a biometric system’s performance: the likelihood of the system incorrectly rejecting an access attempt by an authorized user. While it’s an important metric, it’s not the best overall indicator of accuracy because it doesn’t consider the system’s performance in correctly rejecting unauthorized users. Crossing Error Rate (CER): This is a commonly mistaken term. The correct term is Crossover Error Rate (CER), which is essentially another term for Equal Error Rate.
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The best indicator of the accuracy of a biometric system is the Equal Error Rate (EER) or Crossover Error Rate (CER). This metric represents the point where the False Acceptance Rate (FAR) and False Rejection Rate (FRR) are equal. A lower EER or CER indicates a more accurate biometric system.
Here is a table summarizing the three metrics:
| Metric | Definition |
|---|---|
| False Acceptance Rate (FAR) | The rate at which an unauthorized person is incorrectly accepted as authorized. |
| False Rejection Rate (FRR) | The rate at which an authorized person is incorrectly rejected as unauthorized. |
| Equal Error Rate (EER) | The point where FAR and FRR are equal. |
In addition to EER or CER, other metrics that can be used to assess the accuracy of a biometric system include:
- Genuine Acceptance Rate (GAR): The rate at which an authorized person is correctly accepted as authorized.
- Failure to Enroll Rate (FTE): The rate at which a system is unable to enroll a user.
- Failure to Capture Rate (FTC): The rate at which a system is unable to capture a biometric sample from a user.
- Failure to Extract Rate (FTR): The rate at which a system is unable to extract features from a biometric sample.
- Failure to Identify Rate (FIR): The rate at which a system is unable to identify an individual from a biometric sample.
The choice of which metrics to use to assess the accuracy of a biometric system will depend on the specific application. For example, in a high-security application, a low FAR may be more important than a low FRR. In a low-security application, a low FRR may be more important than a low FAR.
Here are some additional factors that can affect the accuracy of a biometric system:
- Sensor quality: The quality of the sensor used to capture the biometric sample can have a significant impact on the accuracy of the system.
- Biometric template quality: The quality of the biometric template can also have a significant impact on the accuracy of the system.
- Algorithmic performance: The performance of the algorithm used to match biometric samples can also have a significant impact on the accuracy of the system.
- Environmental factors: Environmental factors such as lighting and noise can also affect the accuracy of a biometric system.
Overall, the accuracy of a biometric system is determined by a complex interplay of factors. It is important to carefully consider all of these factors when selecting and deploying a biometric system.