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http://dx.doi.org/10.3807/KJOP.2020.31.3.125

Forensic Classification of Latent Fingerprints Applying Laser-induced Plasma Spectroscopy Combined with Chemometric Methods  

Yang, Jun-Ho (eXtreme Energy Laboratory, Department of Aerospace Engineering, Seoul National University)
Yoh, Jai-Ick (eXtreme Energy Laboratory, Department of Aerospace Engineering, Seoul National University)
Publication Information
Korean Journal of Optics and Photonics / v.31, no.3, 2020 , pp. 125-133 More about this Journal
Abstract
An innovative method for separating overlapping latent fingerprints, using laser-induced plasma spectroscopy (LIPS) combined with multivariate analysis, is reported in the current study. LIPS provides the capabilities of real-time analysis and high-speed scanning, as well as data regarding the chemical components of overlapping fingerprints. These spectra provide valuable chemical information for the forensic classification and reconstruction of overlapping latent fingerprints, by applying appropriate multivariate analysis. This study utilizes principal-component analysis (PCA) and partial-least-squares (PLS) techniques for the basis classification of four types of fingerprints from the LIPS spectra. The proposed method is successfully demonstrated through a classification example of four distinct latent fingerprints, using discrimination such as soft independent modeling of class analogy (SIMCA) and partial-least-squares discriminant analysis (PLS-DA). This demonstration develops an accuracy of more than 85% and is proven to be sufficiently robust. In addition, by laser-scanning analysis at a spatial interval of 125 ㎛, the overlapping fingerprints were separated as two-dimensional forms.
Keywords
LIPS (laser-induced plasma spectroscopy); Latent fingerprint; Overlapping fingerprint; PCA (principal component analysis); Multivariate analysis;
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