Exploration of megapixel hyperspectral LIBS images using principal component analysis

Moncayo, S.; Duponchel, Ludovic; Mousavipak, Niloofar; Panczer, G.; Trichard, Florian; Bousquet, Bruno; Pelascini, Frédéric; Motto-Ros, Vincent

doi:10.1039/c7ja00398f

Cited by 77 publications

(46 citation statements)

References 26 publications

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“…It is important to note that it is still possible that further mineralogical classes are left in the residual matrix E with the remaining noise since, for display purposes, only the first 3 principal components have been used. For further information about LIBS, PCA score maps can be found in the publication of Moncayo et al [12]. The investigation of the remaining variance by using additional principal components is outside the scope of this manuscript.…”

Section: Identification Of the Mineralogical Classesmentioning

confidence: 99%

Ultrafast Elemental Mapping of Platinum Group Elements and Mineral Identification in Platinum-Palladium Ore Using Laser Induced Breakdown Spectroscopy

Rifaï

Özcan²,

Doucet³

et al. 2020

Minerals

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This paper demonstrates the capability of performing an ultrafast chemical mapping of drill cores collected from a platinum/palladium mine using laser-induced breakdown spectroscopy (LIBS). A scan of 40 mm × 30 mm was performed, using a commercial LIBS analyzer, onto the flat surface of a drill core with a scanning speed of 1000 Hz, and a spatial resolution of 50 µm, in about 8 min. Maps of the scanned areas for seven chemical elements (platinum, palladium, nickel, copper, iron, silicon, and magnesium), as well as a single map including the seven elements altogether, were then generated using the proprietary software integrated into the LIBS analyzer. Based on the latter image, seven minerals were identified using the principal component analysis (PCA) and correlations with the elemental maps.

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Section: Identification Of the Mineralogical Classesmentioning

confidence: 99%

Ultrafast Elemental Mapping of Platinum Group Elements and Mineral Identification in Platinum-Palladium Ore Using Laser Induced Breakdown Spectroscopy

Rifaï

Özcan²,

Doucet³

et al. 2020

Minerals

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“…To apply PCA to 3D hyperspectral ginseng matrices, it is necessary to unfold the hypercube into a 2D matrix, in which each column represents all the pixels from a given spectral band in the original image cube, and each row represents the spectrum of a single pixel [18,19]. Furthermore, the PCA was done by applying the following equation:…”

Section: Pca-based Optimal Wavelength Selection For Detecting Whiteningmentioning

confidence: 99%

Near-Infrared Transmittance Spectral Imaging for Nondestructive Measurement of Internal Disorder in Korean Ginseng

Kandpal

Lee

Bae

et al. 2020

Sensors

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The grading of ginseng (Panax ginseng) including the evaluation of internal quality attributes is essential in the ginseng industry for quality control. Assessment for inner whitening, a major internal disorder, must be conducted when identifying high quality ginseng. Conventional methods for detecting inner whitening in ginseng root samples use manual inspection, which is time-consuming and inaccurate. This study develops an internal quality measurement technique using near-infrared transmittance spectral imaging to evaluate inner whitening in ginseng samples. Principle component analysis (PCA) was used on ginseng hypercube data to evaluate the developed technique. The transmittance spectra and spectral images of ginseng samples exhibiting inner whitening showed weak intensity characteristics compared to normal ginseng in the region of 900–1050 nm and 1150–1400 nm respectively, owing to the presence of whitish internal tissues that have higher optical density. On the basis of the multivariate analysis method, even a simple waveband ratio image has the great potential to quickly detect inner whitening in ginseng samples, since these ratio images show a significant difference between whitened and non-whitened regions. Therefore, it is possible to develop an efficient and rapid spectral imaging system for the real-time detection of inner whitening in ginseng using minimal spectral wavebands. This novel strategy for the rapid, cost-effective, non-destructive detection of ginseng’s inner quality can be a key component for the automation of ginseng grading.

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“…This approach, which can be extended to other elements relevant to environmental studies, was regarded as a time-and cost-effective alternative to other methods, such as LA-ICP-MS, for deriving elemental distribution maps. Moncayo et al 285 reported a methodology based on hyperspectral image analysis coupled to PCA for processing large raw data sets of LIBS spectra without spectral pre-processing or any prior knowledge of the sample composition. It was shown to be a powerful tool capable of identifying mineral phases and providing a deeper understanding of the sample, such as highlighting very delicate ion substitution in a mineral lattice.…”

Section: Laser Induced Breakdown Spectroscopymentioning

confidence: 99%

Atomic Spectrometry Update – a review of advances in environmental analysis

Bacon

Butler

Cairns

et al. 2019

J. Anal. At. Spectrom.

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Exploration of megapixel hyperspectral LIBS images using principal component analysis

Abstract: A new methodology based on the well-known principal component analysis, designed for large, raw, and potentially complex dataset, is proposed for the multivariate hyperspectral analysis of LIBS images.

Cited by 77 publications

References 26 publications

Ultrafast Elemental Mapping of Platinum Group Elements and Mineral Identification in Platinum-Palladium Ore Using Laser Induced Breakdown Spectroscopy

Ultrafast Elemental Mapping of Platinum Group Elements and Mineral Identification in Platinum-Palladium Ore Using Laser Induced Breakdown Spectroscopy

Near-Infrared Transmittance Spectral Imaging for Nondestructive Measurement of Internal Disorder in Korean Ginseng

Atomic Spectrometry Update – a review of advances in environmental analysis

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