Novel technological applications for latent and blood-stained fingermark aging studies

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Abstract

At the present time, there are no standard methodologies to reliably determine the age of (latent) fingermarks recovered from crime scenes. Estimating the time of deposition of this type of evidence is a complex challenge that remains scientifically unsolved in the forensic domain. This chapter addresses the effort to investigate and evaluate the age of fingermarks, and answer the question: how much information can “imaging technologies” provide on fingermark aging? The objective is to introduce the reader to novel applications of existing technologies—Optical Profilometry (OP) and visible wavelength Hyperspectral Imaging (HSI)—that can visualize and record variations in the topography of ridges and follow spectral changes in blood-stained fingermarks, respectively. OP has been typically used for the 3D analysis of surface roughness of materials; whereas HSI has been previously used to detect and identify blood stains in a forensic context and estimate their age in laboratory settings. These non-destructive, contactless, imaging technologies eliminate the need for manipulating friction ridge skin impressions and minimizing sample destruction. Most importantly, they allow the simultaneous collection of qualitative and quantitative data that can be analyzed using spatio-temporal statistical models to investigate the mechanisms involved in ridge degradation. OP and HSI, among other technologies, are establishing new foundational research to integrate the age variable in future fingermark examination flowcharts. This inclusion could potentially reduce identification errors that are caused by time inconsistencies between the evidence discovered and the crime committed, as well as maximize the use of resources by decreasing the number of traces to be processed.

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De Alcaraz-Fossoul, J., & Islam, M. (2019). Novel technological applications for latent and blood-stained fingermark aging studies. In Advanced Sciences and Technologies for Security Applications (pp. 33–66). Springer. https://doi.org/10.1007/978-3-030-20542-3_3

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