zhpsЖурнал прикладной спектроскопииZhurnal Prikladnoii Spektroskopii0514-7506B. I. Stepanov Institute of Physics of the National Academy of Scienceszhps-1919Research ArticleАННОТАЦИИ АНГЛОЯЗЫЧНЫХ СТАТЕЙABSTRACTS ENGLISH-LANGUAGE ARTICLESВыявление утрат красочного слоя на древних фресках с помощью дерева решений с индексом износаDeterioration Extraction for Ancient Murals Via a Decision Tree with a Deterioration IndexQiaoK.QiaoK.

Пекин

Kezhen Qiao - School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture; Beijing Key Laboratory for Architectural Heritage Fine Reconstruction and Health Monitoring.

Beijing

HouM.HouM.

Пекин

Miaole Hou - School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture; Beijing Key Laboratory for Architectural Heritage Fine Reconstruction and Health Monitoring.

Beijing

LyuS.LyuS.

Пекин

Shuqiang Lyu - School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture; Beijing Key Laboratory for Architectural Heritage Fine Reconstruction and Health Monitoring.

Beijing

Lvshuqiang@bucea.edu.cnLiL.LiL.

Шаньси

Lihong Li.

Shanxi

Пекинский университет гражданского строительства и архитектуры; Пекинская ключевая лаборатория по реконструкции архитектурного наследия и мониторингу здоровьяBeijing University of Civil Engineering and Architecture; Beijing Key Laboratory for Architectural Heritage Fine Reconstruction and Health MonitoringАкадемия ЮньганYungang Academy202507092025924552552Copyright © Qiao K., Hou M., Lyu S., Li L., 20252025Qiao K., Hou M., Lyu S., Li L.Qiao K., Hou M., Lyu S., Li L.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://zhps.ejournal.by/jour/article/view/1919

Для точного определения областей утрат красочного слоя древних фресок использована гиперспектральная технология. Сначала проанализированы спектральные характеристики области с особым вниманием к красочному слою. Затем для извлечения данных об утрате красочного слоя построено дерево решений с индексом износа. Для этого скомбинированы данные порога отражения в ближней ИК-области и разницы между отражающей способностью при 440 и 490 нм, что делает метод эффективным для получения полной информации об области утраты красочного слоя. Данный подход позволяет получать лучшие визуальные результаты по сравнению с другими традиционными методами извлечения данных. Четкость, отклик, F-критерий и общая точность составили 0.7244, 0.7581, 0.7409 и 0.9680 соответственно. Метод также обладает высокой пороговой стабильностью, что дает возможность получать хорошие результаты при изучении других фресок.

Mural painting is the earliest independent form of painting and involves the crystallization of ancient traditional painting arts. However, over time, various types of deterioration have influenced murals, among which the most common is the deterioration of the plaster layer. Existing extraction methods largely use the shape features obtained from digital images, which are influenced by the diversity of information on the murals. To overcome this drawback, hyperspectral technology was introduced to achieve accurate deterioration extraction. First, the spectral features of deterioration, with a focus on the plaster layer, were analyzed. The decision tree deterioration index was subsequently constructed to extract deterioration information. Combining the threshold of the near-infrared reflectance and the difference between the reflectance at 440 and 490 nm, our method was effective for complete extraction. The method achieved better visual results than other traditional extraction methods did. The precision, recall, F-measure, and overall accuracy were 0.7244, 0.7581, 0.7409, and 0.9680, respectively. Our method also has high threshold stability, yielding good results for other mural images.

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The authors declare that there are no conflicts of interest present.