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Estimating the Data Origin of Fingerprint Samples

机译:估计指纹样本的数据来源

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The data origin (i.e. acquisition technique and acquisition mode) can have a significant impact on the appearance and characteristics of a fingerprint sample. This dataset bias might be challenging for processes like biometric feature extraction. Much effort can be put into data normalization or into processes able to deal with almost any input data. The performance of the former might suffer from this general applicability. The latter losses information by definition. If one is able to reliably identify the data origin of fingerprints, one will be able to dispatch the samples to specialized processes. Six methods of classification are evaluated for their capabilities to distinguish between fifteen different datasets. Acquisition technique and acquisition mode can be classified very accurately. Also, most of the datasets can be distinguished reliably.
机译:数据来源(即采集技术和采集模式)可能会对指纹样本的外观和特性产生重大影响。对于像生物特征提取这样的过程,此数据集偏差可能具有挑战性。可以在数据规范化或几乎可以处理任何输入数据的过程中投入大量精力。前者的性能可能会受到这种普遍适用性的影响。后者根据定义会丢失信息。如果能够可靠地识别指纹的数据来源,则可以将样本分派到专门的流程中。评估了六种分类方法的能力,以区分15种不同的数据集。采集技术和采集模式可以非常准确地分类。而且,大多数数据集都可以可靠地区分。

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