Forensic Comparison of Soil Particles Using Gaussian Mixture Models and Likelihood Ratio Test

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU149800" target="_blank" >RIV/00216305:26220/23:PU149800 - isvavai.cz</a>

Alternative codes found

RIV/00007064:K01__/23:N0000079

Result on the web

<a href="https://ieeexplore.ieee.org/document/10333101" target="_blank" >https://ieeexplore.ieee.org/document/10333101</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICUMT61075.2023.10333101" target="_blank" >10.1109/ICUMT61075.2023.10333101</a>

Result language

angličtina

Original language name

Forensic Comparison of Soil Particles Using Gaussian Mixture Models and Likelihood Ratio Test

Original language description

Forensic analysis of soil traces can be highly valuable in criminal investigation as it can provide evidence which links a person or a contaminated object with one specific location. Given two soil samples, the task of a forensic expert is typically to decide whether they both originate from the same location or not. To confidently answer this question it is necessary to perform a complex analysis focused on examination of the sample’s organic, anthropogenic, and naturally occurrin components. In this paper, we focus on one element of the analysis which studies small mineral particles within the sample. In particular, we propose a novel method for automatic comparison of soil particles, using scanning electron microscope images acquired in the secondary electron (SE) or backscattered electron mode. The method involves segmentation of particles, identification of their contours, and extraction of local descriptors from the images, which are then used to train a sample specific and non-specific Gaussian mixture model (GMM). Finally, a likelihood ratio, based on the GMMs, is calculated to assess the odds that two samples originate from the same location. The proposed method, utilizing Root SIFT descriptors extracted from the SE images along the particle contours, achieved an equal error rate of 13.1% and an area under the curve of 95.2%, surpassing our baseline method derived from particle size analysis.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

50502 - Criminology, penology

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)

ISBN

979-8-3503-9328-6

ISSN

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e-ISSN

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Number of pages

5

Pages from-to

188-192

Publisher name

IEEE Computer Society

Place of publication

neuveden

Event location

Gent, Belgium

Event date

Oct 30, 2023

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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