Red Fluorescent Carbon Dot Powder for Accurate Latent Fingerprint Identification using an Artificial Intelligence Program.,ACS Applied Materials & Interfaces

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Red Fluorescent Carbon Dot Powder for Accurate Latent Fingerprint Identification using an Artificial Intelligence Program.
ACS Applied Materials & Interfaces ( IF 8.3 ) Pub Date : 2020-06-16 , DOI: 10.1021/acsami.0c01972
Xiang-Yang Dong ₁ , Xiao-Qing Niu ₁ , Zheng-Yong Zhang ₂ , Ji-Shi Wei ₁ , Huan-Ming Xiong ₁

Affiliation

Development and comparison of the latent fingerprints (LFPs) are two major studies in detection and identification of LFPs, respectively. However, integrated research studies on both fluorescent materials for LFP development and digital-processing programs for LFP comparison are scarcely seen in the literature. In this work, highly efficient red-emissive carbon dots (R-CDs) are synthesized in one pot and mixed with starch to form R-CDs/starch phosphors. Such phosphors are comparable with various substrates and suitable for the typical powder dusting method to develop LFPs. The fluorescence images of the developed LFPs are handled with an artificial intelligence program. For the optimal sample, this program presents an excellent matching score of 93%, indicating that the developed sample has very high similarity with the standard control. Our results are significantly better than the benchmark obtained by the traditional method, and thus, both the R-CDs/starch phosphors and the digital processing program fit well for the practical applications.

中文翻译：

红色荧光碳点粉末，可使用人工智能程序进行准确的潜在指纹识别。

潜在指纹（LFP）的开发和比较分别是检测和识别LFP的两项主要研究。然而，在文献中几乎没有关于用于LFP开发的荧光材料和用于LFP比较的数字处理程序的综合研究。在这项工作中，在一个锅中合成了高效的红色发光碳点（R-CD），并与淀粉混合形成R-CD /淀粉磷光体。此类磷光体可与各种基材媲美，适用于典型的粉末除尘方法以开发LFP。已开发的LFP的荧光图像通过人工智能程序进行处理。对于最佳样品，该程序的匹配度高达93％，表明开发的样品与标准对照具有很高的相似性。

更新日期：2020-07-01

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