Biometric Security access control systems are designed for recognizing humans based upon one or more unique physical or behavioral characteristics to identify individuals in groups that are under surveillance. The factors used for measuring the performance of any biometric system include accuracy, speed, throughput rate, acceptability to users, uniqueness of the biometric organ and action, resistance to counterfeiting, reliability, data storage requirements, enrollment time, intrusiveness of data collection, and subject and system contact requirements.

Biometric System Performance Metrics

The following are used as performance metrics for biometric systems:

  • False Accept Rate or False Match Rate (FAR or FMR) – The probability that the system incorrectly matches the input pattern to a non-matching template in the database. It measures the percent of invalid inputs which are incorrectly accepted.
  • False Reject Rate or False Non-Match Rate (FRR or FNMR) – The probability that the system fails to detect a match between the input pattern and a matching template in the database. It measures the percent of valid inputs which are incorrectly rejected.
  • Receiver Operating Characteristic or Relative Operating Characteristic (ROC) – The ROC plot is a visual characterization of the trade-off between the FAR and the FRR. In general, the matching algorithm performs a decision based on a threshold which determines how close to a template the input needs to be for it to be considered a match. If the threshold is reduced, there will be less false non-matches but more false accepts. Correspondingly, a higher threshold will reduce the FAR but increase the FRR. A common variation is the Detection error trade-off (DET), which is obtained using normal deviate scales on both axes. This more linear graph illuminates the differences for higher performances (rarer errors).
  • Equal Error Rate or Crossover Error Rate (EER or CER) – The rate at which both accept and reject errors are equal. The value of the EER can be easily obtained from the ROC curve. The EER is a quick way to compare the accuracy of devices with different ROC curves. In general, the device with the lowest EER is most accurate.
  • Failure to Enroll Rate (FTE or FER) – The rate at which attempts to create a template from an input is unsuccessful. This is most commonly caused by low quality inputs.
  • Failure to Capture Rate (FTC) – Within automatic systems, the probability that the system fails to detect a biometric input when presented correctly.
  • Template Capacity – The maximum number of sets of data which can be stored in the system.