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Analysis of slap segmentation and HBSI errors across different force levels

机译:不同力水平下的巴掌分段和HBSI错误分析

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In a recent study, fingerprint data was collected across six different force levels. A total of 8,877 slap samples were ground truthed, and subsequently processed using a commercially available fingerprint segmentation tool. This paper delves deeper into understanding segmentation errors across the force levels. Out of the 8,877 slaps, 370 slaps failed to segment. In order to understand why there were errors, a detailed analysis was undertaken by ground-truthing the slap and segmented datasets. In addition to the ground-truthing, video analysis of the interactions enabled specific failures to be replayed and identified as performance or ergonomic, interaction, and usability (Human Biometric Sensor Interaction) errors. This paper will identify determining factors that would cause the slap segmentation tool to error, and provide guidance to those undertaking data collection activities where they would need to the use a segmentation tool.
机译:在最近的一项研究中,指纹数据是在六个不同的力水平上收集的。总共对8877个拍打样品进行了地面校正,然后使用市售的指纹分割工具进行处理。本文深入研究了跨力水平的分段误差。在8,877拍中,有370拍未能分段。为了理解为什么会出现错误,通过对拍打和分段数据集进行了实地分析,进行了详细的分析。除了真实性之外,对交互的视频分析还可以重播特定的故障,并将其识别为性能或人体工程学,交互和可用性(人类生物特征传感器交互)错误。本文将确定导致拍打分割工具出错的确定因素,并为那些需要使用分割工具进行数据收集活动的人提供指导。

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