A Comparative Study of the Method to Rapid Identification of the Mural Pigments by Combining LIBS-Based Dataset and Machine Learning Methods Article Swipe
Duixiong Sun
,
Yiming Zhang
,
Yaopeng Yin
,
Zhao Zhang
,
Hengli Qian
,
Yarui Wang
,
Zongren Yu
,
Bomin Su
,
Chenzhong Dong
,
Maogen Su
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/chemosensors10100389
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/chemosensors10100389
Due to the similar chemical composition and matrix effect, the accurate identification of mineral pigments on wall paintings has brought great challenges. This work implemented an identification study on three mineral pigments with similar chemical compositions by combining LIBS technology with the K-nearest neighbor algorithm (KNN), random forest (RF support vector machine (SVM), back propagation artificial neural network (Bp-ANN) and convolutional neural network (CNN) to find the most suitable identification method for mural research. Using the SelectKBest algorithm, 300 characteristic lines with the largest difference among the three pigments were determined. The identification models of KNN, RF, SVM, Bp-ANN and CNN were established and optimized. The results showed that, except for the KNN model, the identification accuracy of other models for mock-up mural samples was above 99%. However, only the identification accuracy of 2D-CNN models reached above 94% for actual mural samples. Therefore, the 2D-CNN model was determined as the most suitable model for the identification and analysis of mural pigments.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/chemosensors10100389
- https://www.mdpi.com/2227-9040/10/10/389/pdf?version=1664015773
- OA Status
- gold
- Cited By
- 10
- References
- 36
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4297152853
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- OpenAlex ID
-
https://openalex.org/W4297152853Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/chemosensors10100389Digital Object Identifier
- Title
-
A Comparative Study of the Method to Rapid Identification of the Mural Pigments by Combining LIBS-Based Dataset and Machine Learning MethodsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-09-24Full publication date if available
- Authors
-
Duixiong Sun, Yiming Zhang, Yaopeng Yin, Zhao Zhang, Hengli Qian, Yarui Wang, Zongren Yu, Bomin Su, Chenzhong Dong, Maogen SuList of authors in order
- Landing page
-
https://doi.org/10.3390/chemosensors10100389Publisher landing page
- PDF URL
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https://www.mdpi.com/2227-9040/10/10/389/pdf?version=1664015773Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2227-9040/10/10/389/pdf?version=1664015773Direct OA link when available
- Concepts
-
Mural, Support vector machine, Artificial intelligence, Convolutional neural network, Identification (biology), Artificial neural network, Computer science, Pattern recognition (psychology), Machine learning, Painting, Visual arts, Art, Botany, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
10Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 3, 2024: 3, 2023: 4Per-year citation counts (last 5 years)
- References (count)
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36Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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