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Multisensor hyperspectral imaging approach for the microchemical analysis of ultramarine blue pigments.

ABSTRACT: This work presents a multisensor hyperspectral approach for the characterization of ultramarine blue, a valuable historical pigment, at the microscopic scale combining the information of four analytical techniques at the elemental and molecular levels. The hyperspectral images collected were combined in a single hypercube, where the pixels of the various spectral components are aligned on top of each other. Selected spectral descriptors have been defined to reduce data dimensionality before applying unsupervised chemometric data analysis approaches. Lazurite, responsible for the blue color of the pigment, was detected as the major mineral phase present in synthetic and good quality pigments. Impurities like pyrite were detected in lower quality samples, although the clear identification of other mineral phases with silicate basis was more difficult. There is no correlation between the spatial distribution of the bands arising in the Raman spectra of natural samples in the region 1200-1850 cm^-1 and any of the transition metals or rare earth elements (REE). With this information, the previous hypothesis (based on bulk analysis) attributing these bands to luminescence emissions due to impurities of these elements must be revised. We propose the consideration of CO₂ molecules trapped in the cages of the aluminosilicate structure of sodalite-type. Additionally, correlation between certain Raman features and the combined presence of Ca, P, and REE, in particular Nd, was detected for the lowest quality pigment. Our results highlight the usefulness of fusing chemical images obtained via different imaging techniques to obtain relevant information on chemical structure and properties.

SUBMITTER: Gonzalez-Cabrera M

PROVIDER: S-EPMC8758711 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:This article presents a dataset of hyperspectral images of handwriting samples collected from 54 individuals. The purpose of the presented dataset is to further explore the use of hyperspectral imaging in document image analysis and to benchmark the performance of forensic analysis methods for hyperspectral document images. Each hyperspectral cube in the dataset has a spatial resolution of 512 × 650 pixels and contains 149 spectral channels in the spectral range of 478-901 nm. All the individuals have different personalities and have their writing patterns. The information of age and gender of each individual is collected. Each subject has written twenty-eight sentences using 12 different varieties of pens from different brands in blue color, each approximately 9 words or 33 characters long, all English alphabets in capital and small cases, digits from 0 to 9. The previous methods use synthetic mixed samples created by joining different parts of the images from the UWA WIHSI dataset.Each document consists of real mixed samples written withdifferent pens and by different writers with a variety of mixing ratios of inks and writers for forensic analysis.The standard A4 pages, each weighing 70 gs and manufactured by "AA" company, are used for data collection. The handwritten notes written by each subject with different pens are annotated in rectangular boxes. This dataset can be used for several tasks related to hyperspectral document image analysis and document forensic analysis including, handwritten optical character recognition, ink mismatch detection, writer identification at sentence, word, and character-level, handwriting-based gender classification, handwriting-based age prediction, handwritten word segmentation, and word generation. This dataset was designed and collected by the research team at the Artificial intelligence and Computer Vision Lab (iVision), Institute of Space Technology, Pakistan, and the hyperspectral images were acquired through imaging spectroscopy in the visible wavelength range at Wageningen University & Research, the Netherlands.

Dataset Information

Multisensor hyperspectral imaging approach for the microchemical analysis of ultramarine blue pigments.

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