首页> 外文会议>International Conference on Information Fusion >CMC curve properties and biometric source weighting in multi-biometric score-level fusion
【24h】

CMC curve properties and biometric source weighting in multi-biometric score-level fusion

机译:多生物评分级别融合中的CMC曲线属性和生物特征源加权

获取原文

摘要

Multi-biometrics tries to build a unified biometric decision based on multiple biometric sources in an effort to gain more accuracy and robustness. Multi-biometric fusion aims at optimally combining the information produced by the multiple biometric sources, this usually requires assigning relative weights for the biometric sources to optimize their effect on the final decision. This work presents a new approach for biometric sources weighting within a score-level multi-biometric system. The presented solution tries to investigate the properties of the cumulative match characteristic (CMC) curve, which represents the biometric performance under the identification scenario, and extract biometric source weights based on those properties. The proposed solution is evaluated along with a set of state of the art and best practice weighting techniques. The evaluation was performed on the Biometric Scores Set BSSR1 database and a satisfying and stable performance was achieved.
机译:Multi-biometrics尝试基于多个生物特征来源建立统一的生物特征决策,以期获得更高的准确性和可靠性。多生物特征融合的目的是最佳地组合多个生物特征来源产生的信息,这通常需要为生物特征来源分配相对权重,以优化其对最终决策的影响。这项工作提出了一种新的方法,用于在评分级别的多生物特征系统中对生物特征来源进行加权。提出的解决方案试图研究代表匹配方案下生物特征性能的累积匹配特征(CMC)曲线的特性,并基于这些特性提取生物特征源权重。所提出的解决方案连同一组最新技术和最佳实践加权技术一起进行了评估。在生物特征评分集BSSR1数据库上进行了评估,并获得了令人满意的稳定性能。

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