A method for extracting ancient ceramic patterns based on artificial intelligence
Source abstract
Abstract
To address missing features and reflections in the extraction process of ancient ceramic patterns, a pattern extraction method combining sharpening-smoothing and the whale-type k-means algorithm is proposed. By analyzing the reflection phenomenon of ancient ceramic images, a sharpening-smoothing image enhancement method is designed. It effectively improves image detail and texture expression. In addition, by analyzing the characteristics of missing graphic features in ancient ceramics, a whale-type k-means algorithm is constructed to achieve accurate extraction. The experimental results show that the accuracy of this method in ancient ceramic pattern extraction reaches 99.319%. F1 Score, MIoU, and Recall are 93.13%, 93.84%, and 87.15%, respectively. This method demonstrates superior performance in the accuracy and robustness of ancient ceramic pattern extraction. Meanwhile, it provides reliable technical support for the digital protection of cultural heritage and academic research.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Image Processing and 3D Reconstruction · 3D Shape Modeling and Analysis · Cultural and Historical Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of International Studies, Jingdezhen Ceramic University 1 , Jingdezhen 333403,
School of Mechanical and Electronic Engineering, Jingdezhen Ceramic University 2 , Jingdezhen 333403,
Jiangxi Ceramic Material Processing Technology Engineering Laboratory 3 , Jingdezhen 333403,
Funding
Science and Technology of Jiangxi Provincial Department of Education
References (28)
Show source-provided references
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