Monitoring of illicit pill distribution networks using an image collection exploration framework

Détails

ID Serval
serval:BIB_5FCB9E8816CD
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Monitoring of illicit pill distribution networks using an image collection exploration framework
Périodique
Forensic Science International
Auteur⸱e⸱s
Camargo J., Esseiva P., González F., Wist j., Patiny L.
ISSN
1872-6283
ISSN-L
0379-0738
Statut éditorial
Publié
Date de publication
11/2012
Peer-reviewed
Oui
Volume
223
Numéro
1-3
Pages
298-305
Langue
anglais
Résumé
This paper proposes a novel approach for the analysis of illicit tablets based on their visual characteristics. In particular, the paper concentrates on the problem of ecstasy pill seizure profiling and monitoring. The presented method extracts the visual information from pill images and builds a representation of it, i.e. it builds a pill profile based on the pill visual appearance. Different visual features are used to build different image similarity measures, which are the basis for a pill monitoring strategy based on both discriminative and clustering models. The discriminative model permits to infer whether two pills come from the same seizure, while the clustering models groups of pills that share similar visual characteristics. The resulting clustering structure allows to perform a visual identification of the relationships between different seizures. The proposed approach was evaluated using a data set of 621 Ecstasy pill pictures. The results demonstrate that this is a feasible and cost effective method for performing pill profiling and monitoring.
Mots-clé
Drug intelligence, Image, Ecstasy (XTC), Similarity function, Clustering and visualization
Création de la notice
08/01/2013 14:57
Dernière modification de la notice
20/08/2019 15:17
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