指纹(计算)
可视化
人工智能
模式识别(心理学)
匹配(统计)
化学
细节
计算机视觉
相似性(几何)
特征(语言学)
化学成像
鉴定(生物学)
犯罪现场
超声波传感器
拉曼光谱
分析物
生物系统
指纹识别
计算机科学
Blossom算法
样品(材料)
点云
作者
Yating Zhang,Minlei Liao,Peng Sun,Zhonghan Xu,Bowen Li,Binbin Zhang,Buyi Xu,Rongji Yang,Guoyun Zhou,Chong Wang,Jiujuan Li,Yuanming Chen,ShouXu Wang,Wei He,Yipeng Liu,Yan Hong
标识
DOI:10.1021/acs.analchem.5c07118
摘要
The inadvertent deposition of latent fingerprints stamps indubitable forensic evidence, serving as a solid link between individuals and objective scenes. In this study, a novel approach was developed to simultaneously collect the geometrical and chemical features from latent fingerprints, which establishes a broadened perspective over the inspected biological traces. Ultrasonic spraying was employed to swiftly acquire a uniform distribution of noble metal nanoparticles (NPs) for surface-enhanced Raman spectroscopy (SERS) imaging. The NP-developed fingerprint brings an improved contrast of microscopic visualization as well as additional inelastic spectral information within the SERS image. K-NearestNeighbor (KNN) feature point matching and local similarity matching were utilized to recognize the SERS fingerprint images reconstructed from characteristic SERS bands. A matching score involving minutia descriptors was introduced to parametrize the degree of resemblance in latent fingerprint identification, yielding high matching accuracy even with partially damaged fingerprints. The trade-off between the accuracy in chemical identification and the completeness in fingerprint reconstruction was discussed. The effective SERS visualization and reconstruction of fingerprints was accomplished from the sample containing etomidate with the concentration as low as 1 μM. Additionally, the SERS imaging on a curved keycap surface was realized, which meets the critical demands of the investigation over particular chemicals.
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