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Pre-processing methods for automatic pigment recognition through Vis–NIR reflectance spectra

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Abstract

The present work introduces the preliminary outcome of one of the tasks inside the MOBARTECH project, that is the creation of the prototype for a compact FORS spectrophotometer capable of automatically identifying pigments and dyes. On the road toward this goal, we focused on the automation of pigment identification, as aspect of great interest which would allow real time analysis with benefit especially for unskilled operators. In this paper, we evaluate high-order derivative approximation pre-processing and features extraction methods, strictly related to the way the database is built; we have chosen to use a dynamic database to be able to elaborate data and give an answer in real time, independently from the experimental set up, and we are planning an interface suitable for both non-skilled and expert users. The aim of the present research is thus to evaluate how spectra pre-processing affects the response and the ability of the search algorithm to correctly identify an unknown spectrum, in order to develop a totally automated pipeline for spectra identification or to prefer an interactive framework.

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Data Availability Statement

This manuscript has associated data in a data repository. [Authors’ comment: The original data and spectra used in this work are available from the corresponding author on request.]

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Acknowledgements

This work was supported by Regione Lombardia (Italy) in the framework of the Project “MOBARTECH: una piattaforma mobile tecnologica, interattiva e partecipata per lo studio, la conservazione e la valorizzazione di beni storico-artistici—Call Accordi per la Ricerca e l’Innovazione”. The authors thank the restores from Pinacoteca di Brera for support during data acquisition in situ.

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Authors and Affiliations

  1. Dipartimento di Scienze della Terra “Ardito Desio”, Università degli Studi di Milano, via Mangiagalli 34, 20133, Milano, Italy

    Jacopo Melada

  2. Dipartimento di Fisica “Aldo Pontremoli”, Università degli Studi di Milano, Via Celoria 16, 20133, Milano, Italy

    Letizia Bonizzoni, Marco Gargano, Emanuela Grifoni & Nicola Ludwig

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  1. Jacopo Melada
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  2. Letizia Bonizzoni
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  3. Marco Gargano
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  4. Emanuela Grifoni
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  5. Nicola Ludwig
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Corresponding author

Correspondence to Letizia Bonizzoni.

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Melada, J., Bonizzoni, L., Gargano, M. et al. Pre-processing methods for automatic pigment recognition through Vis–NIR reflectance spectra. Eur. Phys. J. Plus 137, 44 (2022). https://doi.org/10.1140/epjp/s13360-021-02262-6

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