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Context-based approach of separating contactless captured high-resolution overlapped latent fingerprints

机译:基于上下文的分离非接触式捕获的高分辨率重叠潜在指纹的方法

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摘要

Overlapped latent fingerprints occurring at crime scenes challenge forensic investigations, as they cannot be properly processed unless separated. Addressing this, Chen et al. proposed a relaxation-labelling-based approach on simulated samples, improved by Feng et al. for conventionally developed latent ones. As the development of advanced contactless nanometrerange sensing technology keeps broadening the vision of forensics, the authors use a chromatic white light sensor for contactless non-invasive acquisition. This preserves the fingerprints for further investigations and enhances existing separation techniques. Motivated by the trend in dactyloscopy that investigations now not only aim at identifications but also retrieving further context of the fingerprints (e.g. chemical composition, age), a context-based separation approach is suggested for highresolution samples of overlapped latent fingerprints. The author??s conception of context-aware data processing is introduced to analyse the context in this forensic scenario, yielding an enhanced separation algorithm with optimised parameters. Two test sets are generated for evaluation, one consisting of 60 authentic overlapped fingerprints on three substrates and the other of 100 conventionally developed latent samples from the work of Feng et al. An equal error rate of 5.7% is achieved on the first test set, which shows improvement over their previous work, and 17.9% on the second.
机译:在犯罪现场发生的重叠的潜在指纹挑战了法医调查,因为除非将它们分开就无法正确处理。对此,Chen等人。 Feng等人提出了一种基于松弛标记的模拟样本方法,并得到了Feng等人的改进。适用于常规开发的潜在产品。随着先进的非接触式纳米范围传感技术的发展不断拓宽法医的视野,作者将彩色白光传感器用于非接触式非侵入式采集。这保留了指纹以供进一步研究,并增强了现有的分离技术。由于指纹学趋势的发展,现在的研究不仅针对鉴定,而且还检索指纹的其他背景信息(例如化学成分,年龄),因此建议对重叠的潜在指纹的高分辨率样本使用基于背景的分离方法。引入了作者的上下文感知数据处理的概念来分析这种取证场景中的上下文,从而产生具有优化参数的增强分离算法。生成了两个测试集进行评估,一个由三个基材上的60个真实的重叠指纹组成,另一个由Feng等人的工作中的100个常规开发的潜在样本组成。第一个测试集的平均错误率达到5.7%,这表明他们比以前的测试有所改进,而第二个测试集的错误率达到17.9%。

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  • 来源
    《Biometrics, IET》 |2014年第2期|101-112|共12页
  • 作者单位

    Faculty of Computer Science, Otto von Guericke University Magdeburg, Magdeburg, Germany|c|;

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  • 正文语种 eng
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