• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>2016 International Conference on Biometrics >Bayesian Belief models for integrating match scores with liveness and quality measures in a fingerprint verification system
【24h】

Bayesian Belief models for integrating match scores with liveness and quality measures in a fingerprint verification system

机译：贝叶斯信念模型，用于在指纹验证系统中将比赛得分与活动性和质量度量相集成

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Recent research has sought to improve the resilience of fingerprint verification systems to spoof attacks by combining match scores with both liveness measures and image quality in a learning-based fusion framework. Designing such a fusion framework is challenging because quality and liveness measures can impact the match scores and, therefore, the influence of these variables on the match score has to be modelled. Further, these measures themselves are influenced by many latent factors, such as the fabrication material used to generate fake fingerprints. We advance the state-of-the-art by proposing two Bayesian Belief Network (BBN) models that can utilize these measures effectively, by appropriately modelling the relationship between quality, liveness measure and match scores with the consideration of latent variables. We demonstrate the efficacy of the proposed models on the LivDet 2011 fingerprint spoof dataset.
机译：最近的研究试图通过在基于学习的融合框架中将匹配分数与活跃度和图像质量相结合，来提高指纹验证系统对欺骗攻击的弹性。设计这样的融合框架具有挑战性，因为质量和活动性度量会影响比赛得分，因此，必须对这些变量对比赛得分的影响进行建模。此外，这些措施本身还受许多潜在因素的影响，例如用于生成假指纹的制造材料。我们通过提出两个可以有效利用这些度量的贝叶斯信念网络（BBN）模型，并通过对质量，活动性度量和匹配分数之间的关系进行建模，并考虑潜在变量，从而提高了技术水平。我们在LivDet 2011指纹欺骗数据集上证明了所提出模型的功效。

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