ArticleSensors (Basel, Switzerland)2020
Evaluation of Cleaning Processes Using Colorimetric and Spectral Data for the Removal of Layers of Limewash from Medieval Plasterwork.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 14 citations in OpenAlex.
- Colorimetric Evaluation of a Reintegration via Spectral Imaging-Case Study: Nasrid Tiling Panel from the Alhambra of Granada (Spain).Sensors (Basel, Switzerland) · 2024Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
In the cultural heritage preservation of medieval buildings, it is common to find plaster walls covered in lime, which previously were painted in polychromy. The conservation interventions usually try to remove the whitewash, whilst maintaining the original color of the painted wall as much as possible. However, there is no agreement on which cleaning technique best preserves the original appearance of the colored plaster. Different pigments found below the lime layer may behave differently depending on the cleaning technique used. Usually, colorimetric or photometric area-based measurements are carried out to study the color of the cleaned areas to compare with their original color, obtained from pre-made plaster probes. However, this methodology fails when the mean color difference is not enough to fully characterize the changes in texture and color appearance. This study presents a set of experiments carried out using two different pigments (cinnabar and malachite) covered with lime, and treated with nine different cleaning techniques on plaster probes prepared according to medieval techniques. We have studied the effect of the cleaning process on the color and the homogeneity of the samples using a hyperspectral imaging workflow. Four different analysis methods are presented and discussed. Our results show that the proposed analysis is able to provide a much more comprehensive and diversified characterization of the quality of the cleaning method compared to the commonly used colorimetric or photometric area-based measurements.
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