School of Computer Science and Technology, Shandong University, Jinan 250101, Shandong, China.
Sensors (Basel). 2013 Sep 4;13(9):11660-86. doi: 10.3390/s130911660.
Conventional fingerprint verification systems use only static information. In this paper, fingerprint videos, which contain dynamic information, are utilized for verification. Fingerprint videos are acquired by the same capture device that acquires conventional fingerprint images, and the user experience of providing a fingerprint video is the same as that of providing a single impression. After preprocessing and aligning processes, "inside similarity" and "outside similarity" are defined and calculated to take advantage of both dynamic and static information contained in fingerprint videos. Match scores between two matching fingerprint videos are then calculated by combining the two kinds of similarity. Experimental results show that the proposed video-based method leads to a relative reduction of 60 percent in the equal error rate (EER) in comparison to the conventional single impression-based method. We also analyze the time complexity of our method when different combinations of strategies are used. Our method still outperforms the conventional method, even if both methods have the same time complexity. Finally, experimental results demonstrate that the proposed video-based method can lead to better accuracy than the multiple impressions fusion method, and the proposed method has a much lower false acceptance rate (FAR) when the false rejection rate (FRR) is quite low.
传统的指纹验证系统仅使用静态信息。本文利用包含动态信息的指纹视频进行验证。指纹视频由获取常规指纹图像的相同采集设备获取，用户提供指纹视频的体验与提供单个指纹图像的体验相同。经过预处理和对齐过程，定义并计算了“内部相似性”和“外部相似性”，以利用指纹视频中包含的动态和静态信息。然后，通过组合这两种相似性来计算两个匹配的指纹视频之间的匹配得分。实验结果表明，与传统的基于单个指纹图像的方法相比，所提出的基于视频的方法可将错误接受率（EER）相对降低 60%。我们还分析了当使用不同策略组合时，我们的方法的时间复杂度。即使两种方法的时间复杂度相同，我们的方法仍然优于传统方法。最后，实验结果表明，与多指纹融合方法相比，所提出的基于视频的方法可以获得更好的准确性，并且当错误拒绝率（FRR）相当低时，所提出的方法的错误接受率（FAR）要低得多。
