Discrimination and identification of RDX/PETN explosives by chemometrics applied to terahertz time-domain spectral imaging
| العنوان: | Discrimination and identification of RDX/PETN explosives by chemometrics applied to terahertz time-domain spectral imaging |
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| المؤلفون: | Patrick Mounaix, Bruno Bousquet, Norbert Palka, J. Bou-Sleiman, Jean-Baptiste Perraud, Jean-Paul Guillet |
| المساهمون: | Laboratoire de l'intégration, du matériau au système (IMS), Université Sciences et Technologies - Bordeaux 1 (UB)-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS), Centre d'Etudes Lasers Intenses et Applications (CELIA), Université de Bordeaux (UB)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS), Université Sciences et Technologies - Bordeaux 1-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Bordeaux (UB) |
| المصدر: | VIII Millimetre Wave and Terahertz Sensors and Technology conference VIII Millimetre Wave and Terahertz Sensors and Technology conference, Sep 2015, Toulouse, France. ⟨10.1117/12.2197442⟩ |
| بيانات النشر: | SPIE, 2015. |
| سنة النشر: | 2015 |
| مصطلحات موضوعية: | Chemical imaging, Principal Component Analysis, Chemometric approach, medicine.medical_specialty, Materials science, Explosive material, business.industry, Terahertz, Analytical chemistry, Hyperspectral imaging, Pattern recognition, Terahertz spectroscopy and technology, Spectral imaging, Chemometrics, [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, Imaging spectroscopy, Principal component analysis, medicine, Artificial intelligence, business |
| الوصف: | International audience; Detection of explosives has always been a priority for homeland security. Jointly, terahertz spectroscopy and imaging are emerging and promising candidates as contactless and safe systems. In this work, we treated data resulting from hyperspectral imaging obtained by THz-time domain spectroscopy, with chemometric tools. We found efficient identification and sorting of targeted explosives in the case of pure and mixture samples. In this aim, we applied to images Principal Component Analysis (PCA) to discriminate between RDX, PETN and mixtures of the two materials, using the absorbance as the key-parameter. Then we applied Partial Least Squares-Discriminant Analysis (PLS-DA) to each pixel of the hyperspectral images to sort the explosives into different classes. The results clearly show successful identification and categorization of the explosives under study. |
| تدمد: | 0277-786X |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c78a73eb42f089a34554cb62a27f072 https://doi.org/10.1117/12.2197442 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....4c78a73eb42f089a34554cb62a27f072 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 0277786X |
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