论文标题
关于指纹识别的人口偏见
On Demographic Bias in Fingerprint Recognition
论文作者
论文摘要
指纹识别系统已在全球范围内部署在许多应用程序中，包括个人设备，取证，执法，银行业和国家身份系统。对于这些系统在社会上可接受和值得信赖，至关重要的是，它们在不同的人群群体中表现良好。在这项工作中，我们提出了一个形式的统计框架，以测试四个主要人口组（白人男性，白人女性，黑人男性，黑人男性和黑人女性）在指纹识别中存在偏见（人口统计学差异），以在验证和识别模式下运行的两个先进的（SOTA）指纹匹配者。在两个不同的指纹数据库（有15,468和1,014名受试者）上进行的实验表明，随着匹配器的精度的提高，SOTA指纹识别系统中的人口统计学差异降低，并且可能明显的任何小偏见可能是由于某些较小的偏见，这是由于某些较小的较低的，低质的指纹图像。
Fingerprint recognition systems have been deployed globally in numerous applications including personal devices, forensics, law enforcement, banking, and national identity systems. For these systems to be socially acceptable and trustworthy, it is critical that they perform equally well across different demographic groups. In this work, we propose a formal statistical framework to test for the existence of bias (demographic differentials) in fingerprint recognition across four major demographic groups (white male, white female, black male, and black female) for two state-of-the-art (SOTA) fingerprint matchers operating in verification and identification modes. Experiments on two different fingerprint databases (with 15,468 and 1,014 subjects) show that demographic differentials in SOTA fingerprint recognition systems decrease as the matcher accuracy increases and any small bias that may be evident is likely due to certain outlier, low-quality fingerprint images.
