Quantifying the weight of fingerprint evidence through the spatial relationship, directions and types of minutiae observed on fingermarks

Details

Serval ID
serval:BIB_C6AD6B03DA11
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Quantifying the weight of fingerprint evidence through the spatial relationship, directions and types of minutiae observed on fingermarks
Journal
Forensic Science International
Author(s)
Neumann C., Champod C., Yoo M., Genessay T., Langenburg G.
ISSN
0379-0738
Publication state
Published
Issued date
03/2015
Peer-reviewed
Oui
Volume
248
Pages
154-171
Language
french
Abstract
This paper presents a statistical model for the quantification of the weight of fingerprint evidence. Contrarily to previous models (generative and score-based models), our model proposes to estimate the probability distributions of spatial relationships, directions and types of minutiae observed on fingerprints for any given fingermark. Our model is relying on an AFIS algorithm provided by 3M Cogent and on a dataset of more than 4,000,000 fingerprints to represent a sample from a relevant population of potential sources. The performance of our model was tested using several hundreds of minutiae configurations observed on a set of 565 fingermarks. In particular, the effects of various sub-populations of fingers (i.e., finger number, finger general pattern) on the expected evidential value of our test configurations were investigated.
The performance of our model indicates that the spatial relationship between minutiae carries more evidential weight than their type or direction. Our results also indicate that the AFIS component of our model directly enables us to assign weight to fingerprint evidence without the need for the additional layer of complex statistical modeling involved by the estimation of the probability distributions of fingerprint features. In fact, it seems that the AFIS component is more sensitive to the sub-population effects than the other components of the model.
Overall, the data generated during this research project contributes to support the idea that fingerprint evidence is a valuable forensic tool for the identification of individuals.
Keywords
Fingerprint evidence, Strength of evidence, Sub-population effect, Spatial relationship, Statistical model
Create date
24/02/2015 8:20
Last modification date
20/08/2019 15:42
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