A new fingerprint parameterization for liveness detection based on quality measures is presented. The novel feature set is used in a complete liveness detection system and tested on the development set of the LivDET competition, comprising over 4,500 real and fake images acquired with three different optical sensors. The proposed solution proves to be robust to the multi-sensor scenario, and presents an overall rate of 93% of correctly classified samples. Furthermore, the liveness detection method presented has the added advantage over previously studied techniques of needing just one image from a finger to decide whether it is real or fake.
翻译：展示了基于质量计量的活性检测新指纹参数。新特征集用于完整的活性检测系统,并测试了LivDET竞赛的成套开发,包括用三种不同光感传感器获得的4 500多张真实和假图像。拟议解决方案证明对多传感器情景是可靠的,并提供了93%的正确分类样本的总体率。此外,所提出的活性检测方法比以往研究的只需要一根手指图像来确定是真实还是假的技巧更具优势。
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