Objective color classification of ecstasy tablets by hyperspectral imaging

التفاصيل البيبلوغرافية
العنوان: Objective color classification of ecstasy tablets by hyperspectral imaging
المؤلفون: Maurice C. G. Aalders, Martin Lopatka, Gerda J. Edelman
المساهمون: Other departments, Other Research, Biomedical Engineering and Physics
المصدر: Journal of forensic sciences, 58(4), 881-886. Wiley-Blackwell
سنة النشر: 2012
مصطلحات موضوعية: genetic structures, business.industry, Ecstasy, Analytical chemistry, Hyperspectral imaging, Pattern recognition, Kubelka munk, Reflectivity, Pathology and Forensic Medicine, Photon propagation, Reference measurement, Genetics, Color measurement, Artificial intelligence, business, Mathematics
الوصف: The general procedure followed in the examination of ecstasy tablets for profiling purposes includes a color description, which depends highly on the observers' perception. This study aims to provide objective quantitative color information using visible hyperspectral imaging. Both self-manufactured and illicit tablets, created with different amounts of known colorants were analyzed. We derived reflectance spectra from hyperspectral images of these tablets, and successfully determined the most likely colorant used in the production of all self-manufactured tablets and four of five illicit tablets studied. Upon classification, the concentration of the colorant was estimated using a photon propagation model and a single reference measurement of a tablet of known concentration. The estimated concentrations showed a high correlation with the actual values (R(2) = 0.9374). The achieved color information, combined with other physical and chemical characteristics, can provide a powerful tool for the comparison of tablet seizures, which may reveal their origin.
تدمد: 1556-4029
0022-1198
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e89515c3f79e5e50d420d27a02b5174e
https://pubmed.ncbi.nlm.nih.gov/23683098
Rights: RESTRICTED
رقم الانضمام: edsair.doi.dedup.....e89515c3f79e5e50d420d27a02b5174e
قاعدة البيانات: OpenAIRE