Automatic Measures for Predicting Performance in Off-Line Signature

Performance in terms of accuracy is one of the most important goal of a biometric system. Hence, having a measure which is able to predict the performance with respect to a particular sample of interest is specially useful, and can be exploited in a number of ways. In this paper, we present two automatic measures for predicting the performance in off-line signature verification. Results obtained on a sub-corpus of the MCYT signature database confirms a relationship between the proposed measures and system error rates measured in terms of Equal Error Rate (EER), False Acceptance Rate (FAR) and False Rejection Rate (FRR). 1

• Type: Conference
• Year: 2007
• Where: ICIP
• Authors: Fernando Alonso-Fernandez, Michael C. Fairhurst, Julian Fiérrez-Aguilar, Javier Ortega-Garcia
• Keywords: Equal Error Rate, Error Rate, False Acceptance Rate, ICIP 2007, Image Processing