Sum of Group Error Differences: A Critical Examination of Bias Evaluation in Biometric Verification and a Dual-Metric Measure

arXiv:2404.15385v1 Announce Type: new
Abstract: Biometric Verification (BV) systems often exhibit accuracy disparities across different demographic groups, leading to biases in BV applications. Assessing and quantifying these biases is essential for ensuring the fairness of BV systems. However, existing bias evaluation metrics in BV have limitations, such as focusing exclusively on match or non-match error rates, overlooking bias on demographic groups with performance levels falling between the best and worst performance levels, and neglecting the magnitude of the bias present. …

abstract accuracy applications arxiv bias biases biometric cs.ai cs.cv cs.cy differences error evaluation evaluation metrics fairness however metrics sum systems type verification