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

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 pigme...

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Bibliographic Details
Published in:European physical journal plus 2022-01, Vol.137 (1), p.44, Article 44
Main Authors: Melada, Jacopo, Bonizzoni, Letizia, Gargano, Marco, Grifoni, Emanuela, Ludwig, Nicola
Format: Article
Language:English
Subjects:
Algorithms
Applications and Case Studies
Applied and Technical Physics
Approximation
Atomic
Automation
Classification
Complex Systems
Condensed Matter Physics
Cultural heritage
Focus Point on Advances in Photonics for Heritage Science: Developments
Identification
Libraries
Machine learning
Mathematical and Computational Physics
Methods
Molecular
Neural networks
Operators (mathematics)
Optical and Plasma Physics
Physics
Physics and Astronomy
Pigments
Real time
Regular Article
Search algorithms
Similarity measures
Spectra
Theoretical
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Summary: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.
ISSN:2190-5444
2190-5444
DOI:10.1140/epjp/s13360-021-02262-6