{"title":"Extraction method of Yuan blue and white porcelain pattern based on multi-scale Retinex and histogram multi-peak threshold segmentation","authors":"Qi Zheng, Baoxi Zhu, Qin Cai, Jiao Li, Changfu Fang, Nanxing Wu","doi":"10.1186/s40494-024-01324-z","DOIUrl":null,"url":null,"abstract":"<p>Aiming at the problem of \"crystallization\" on the surface of Yuan blue and white ceramics, which causes reflections and loss of image texture, an image processing method is proposed to repair the image texture information. A multi-scale Retinex pre-processing method is proposed to enhance the contrast between the pattern and the background. A color factor is introduced to prevent color distortion. A weighted average function is constructed to enhance image details and improve texture information. The Yuan blue and white pattern can be effectively segmented from the background using a combination of multi-peak thresholding for segmentation and other techniques. The experimental results demonstrate that, in comparison to other algorithms, the multi-scale Retinex and histogram multi-peak threshold coupled segmentation method proposed in this paper exhibits the highest F1-score of 0.03067 and an accuracy of 92.67% in cross-evaluation with other algorithms. This indicates that the overall performance of the algorithm is the best. The proposed method has the potential to inform the protection of cultural relics.</p>","PeriodicalId":13109,"journal":{"name":"Heritage Science","volume":"66 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Heritage Science","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1186/s40494-024-01324-z","RegionNum":1,"RegionCategory":"艺术学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Aiming at the problem of "crystallization" on the surface of Yuan blue and white ceramics, which causes reflections and loss of image texture, an image processing method is proposed to repair the image texture information. A multi-scale Retinex pre-processing method is proposed to enhance the contrast between the pattern and the background. A color factor is introduced to prevent color distortion. A weighted average function is constructed to enhance image details and improve texture information. The Yuan blue and white pattern can be effectively segmented from the background using a combination of multi-peak thresholding for segmentation and other techniques. The experimental results demonstrate that, in comparison to other algorithms, the multi-scale Retinex and histogram multi-peak threshold coupled segmentation method proposed in this paper exhibits the highest F1-score of 0.03067 and an accuracy of 92.67% in cross-evaluation with other algorithms. This indicates that the overall performance of the algorithm is the best. The proposed method has the potential to inform the protection of cultural relics.
期刊介绍:
Heritage Science is an open access journal publishing original peer-reviewed research covering:
Understanding of the manufacturing processes, provenances, and environmental contexts of material types, objects, and buildings, of cultural significance including their historical significance.
Understanding and prediction of physico-chemical and biological degradation processes of cultural artefacts, including climate change, and predictive heritage studies.
Development and application of analytical and imaging methods or equipments for non-invasive, non-destructive or portable analysis of artwork and objects of cultural significance to identify component materials, degradation products and deterioration markers.
Development and application of invasive and destructive methods for understanding the provenance of objects of cultural significance.
Development and critical assessment of treatment materials and methods for artwork and objects of cultural significance.
Development and application of statistical methods and algorithms for data analysis to further understanding of culturally significant objects.
Publication of reference and corpus datasets as supplementary information to the statistical and analytical studies above.
Description of novel technologies that can assist in the understanding of cultural heritage.