首页> 外文会议>2012 IEEE International Workshop on Information Forensics and Security. >Can a “poor” verification system be a “good” identification system? A preliminary study
【24h】

Can a “poor” verification system be a “good” identification system? A preliminary study

机译:“不良”验证系统可以成为“良好”识别系统吗?初步研究

获取原文
获取原文并翻译 | 示例

摘要

The matching accuracy of a biometric system is typically quantified through measures such as the False Match Rate (FMR), False Non-match Rate (FNMR), Equal Error Rate (EER), Receiver Operating Characteristic (ROC) curve and Cumulative Match Characteristic (CMC) curve. In this work, we analyze the relationship between the ROC and CMC curves, which are two measures commonly used to describe the performance of verification and identification systems, respectively. We establish that it is possible for a biometric system to exhibit “good” verification performance and “poor” identification performance (and vice versa) by demonstrating the conditions required to produce such outcomes. Experimental analysis using synthetically generated match scores confirms our hypothesis that the ROC or CMC alone cannot completely characterize biometric system performance.
机译:生物识别系统的匹配精度通常通过错误匹配率(FMR),错误不匹配率(FNMR),均等错误率(EER),接收器工作特征(ROC)曲线和累积匹配特征( CMC)曲线。在这项工作中,我们分析了ROC和CMC曲线之间的关系,这是分别用来描述验证和识别系统性能的两种度量。我们证明,通过证明产生这种结果所需的条件,生物识别系统有可能表现出“良好”的验证性能和“不良”的识别性能(反之亦然)。使用合成生成的匹配分数进行的实验分析证实了我们的假设,即仅ROC或CMC不能完全表征生物识别系统的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号