Scholarlink

This project focuses on determining the composition and concentration of unknown pigment mixtures using Kubelka-Munk theory and spectro-colorimetric analysis, extended with advanced mathematics and AI. Tests were conducted on five selected acrylic commercial colours (Südor) to evaluate an algorithm based on the modified Kubelka-Munk equation. The pigments were characterized by their spectral absorbance, reflectance, and scattering values partially directly measured (spectral reflectance) with a spectroradiometer, and partially using the K-M modified equations. Spectral Imaging of the painting was captured and calibrated applying an AI-based software SpectraPick, developed by Profilocolore Srl. Analyses of single pigment or mix of them were conducted using PickViewer software (Profilocolore), which includes the modified K-M equations for pigment mix analysis and a pigment Database of spectral reflectance, scattering and absorbance, and colorimetry for each pigment. The software allows to select points on the painting and suggests the most likely used pigments and their percentage. The results obtained show very good matching between pigment mix identified by the system and the real mix submitted to it. The pigment database was expanded with commercial colours used in the restoration field (Zecchi and Kremer), based on different mediums, respectively yolk and linseed oil. Tests were carried out on their mixtures, to confirm the consistency of the enhanced modified algorithms.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Innovative, Non-invasive Approach for Pigment Mixtures Characterization Based on Kubelka – Munk Theory and Spectroscopy

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Hélène Aureli,
  • Matteo Fois,
  • Elisa Agostini,
  • Marco Muzi,
  • Damiano Scalabrin,
  • Carmen Covarelli,
  • Ottaviano Caruso,
  • Marcello Melis

摘要

This project focuses on determining the composition and concentration of unknown pigment mixtures using Kubelka-Munk theory and spectro-colorimetric analysis, extended with advanced mathematics and AI. Tests were conducted on five selected acrylic commercial colours (Südor) to evaluate an algorithm based on the modified Kubelka-Munk equation. The pigments were characterized by their spectral absorbance, reflectance, and scattering values partially directly measured (spectral reflectance) with a spectroradiometer, and partially using the K-M modified equations. Spectral Imaging of the painting was captured and calibrated applying an AI-based software SpectraPick, developed by Profilocolore Srl. Analyses of single pigment or mix of them were conducted using PickViewer software (Profilocolore), which includes the modified K-M equations for pigment mix analysis and a pigment Database of spectral reflectance, scattering and absorbance, and colorimetry for each pigment. The software allows to select points on the painting and suggests the most likely used pigments and their percentage. The results obtained show very good matching between pigment mix identified by the system and the real mix submitted to it. The pigment database was expanded with commercial colours used in the restoration field (Zecchi and Kremer), based on different mediums, respectively yolk and linseed oil. Tests were carried out on their mixtures, to confirm the consistency of the enhanced modified algorithms.