Automated mold defects classification in paintings: A comparison of machine learning and rule-based techniques.
Mold defects pose a significant risk to the preservation of valuable fine art paintings, typically arising from fungal growth in humid environments. This paper presents a novel approach for detecting and categorizing mold defects in fine art paintings. The technique leverages a feature extraction me...
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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2025-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0316996 |
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