Algorithm Performance Evaluation

The parameters adopted for the performance evaluation will be the following:

Evaluation per sensor sub-set

• Frej_n: Rate of failure to enroll for the sub-set n
• Fcorrlive_n: Rate of correctly classified live fingerprints for sub-set n
• Fcorrfake_n: Rate of correctly classified fake fingerprints for sub-set n
• Ferrlive_n: Rate of misclassified live fingerprints for sub-set n
• Ferrfake_n: Rate of misclassified fake fingerprints for sub-set n
• ET: Average processing time per image
• MAM: Max. Allocated Memory while the algorithm is running

Rates are based on the assumption of a threshold of 50.

Overall evaluation based on average across the three sensors

• Frej: Rate of failure to enroll
• Fcorrlive: Rate of correctly classified live fingerprints
• Fcorrfake_n: Rate of correctly classified fake fingerprints
• Ferrlive_n: Rate of misclassified live fingerprints
• Ferrfake_n: Rate of misclassified fake fingerprints

Declaration of the Winner

• The winner will be awarded by minimum of the average of the overall classification errors on the three sensors. Only one winner will be awarded.