Surface granularity as a discriminating feature of illicit tablets

Details

Serval ID
serval:BIB_AFA65F8C3D9A
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Surface granularity as a discriminating feature of illicit tablets
Journal
Forensic Science International
Author(s)
Lopatka M., Vallat M.
ISSN
1872-6283
Publication state
Published
Issued date
07/2011
Peer-reviewed
Oui
Volume
210
Number
1-3
Pages
188-200
Language
english
Abstract
In this paper we propose an innovative methodology for automated profiling of illicit tablets bytheir surface granularity; a feature previously unexamined for this purpose. We make use of the tinyinconsistencies at the tablet surface, referred to as speckles, to generate a quantitative granularity profileof tablets. Euclidian distance is used as a measurement of (dis)similarity between granularity profiles.The frequency of observed distances is then modelled by kernel density estimation in order to generalizethe observations and to calculate likelihood ratios (LRs). The resulting LRs are used to evaluate thepotential of granularity profiles to differentiate between same-batch and different-batches tablets.Furthermore, we use the LRs as a similarity metric to refine database queries. We are able to derivereliable LRs within a scope that represent the true evidential value of the granularity feature. Thesemetrics are used to refine candidate hit-lists form a database containing physical features of illicittablets. We observe improved or identical ranking of candidate tablets in 87.5% of cases when granularityis considered.
Keywords
Illicit tablets, Granularity, Ecstasy (XTC), Likelihood ratio, Features, Image processing
Create date
04/08/2011 6:27
Last modification date
20/08/2019 15:19
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