The digital restoration of painted patterns on the No. 2 Qin bronze chariot based on hyperspectral imaging
Dados Bibliográficos
| ID | 8352152 |
|---|---|
| Autores | Dong Han (0000-0002-1150-9748, Tianjin University), Liying Ma (0000-0002-7186-8259, Tianjin University), Shengtao Ma (0000-0001-8959-4260, Shaanxi History Museum), Jiawan Zhang (0000-0002-0667-6744, Tianjin University, autor correspondente) |
| Ano | 2020 |
| Volume | 62 |
| Fascículo | 1 |
| Páginas | 200-212 |
| Data de publicação | 2020-02-01 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Archaeometry (JOURNAL) |
| Identificadores do periódico | ISSN: 0003-813X • E-ISSN: 1475-4754 |
| Editora | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/arcm.12516 |
| OpenAlex | W2985693396 |
| Idioma | EN |
| Citações recebidas | 3 |
| Referências citadas | 20 |
The No. 2 Qin bronze chariot unearthed from Qinshihuang's Mausoleum is world famous for its huge size and colourful painted patterns. However, since it had been buried for a long time and was affected by its harsh environment, its painted patterns have been severely damaged. The traditional restoration methods, which mainly rely on expert experience, are manual, inefficient and lack scientific support. Moreover, to protect the important cultural relics, any invasive operations, such as sampling analysis, are strictly prohibited. This paper presents a method that combines hyperspectral imaging and computer technology for the digital virtual restoration of the bronze chariot's patterns. It is non‐destructive, more efficient and more scientific. The method reproduces the damaged patterns with the following approaches: restoring the missing edges of the patterns; and distinguishing the different pigments. The obtained result implies that the method can digitally reproduce some of the damaged patterns, and that it can be used as a reference for recreating the patterns of the other painted bronze
Archaeology · Art · Bronze · Chariot · Geography · Hyperspectral imaging · Artificial Intelligence · Computer Science · Cultural Heritage Materials Analysis · Geochemistry and Geologic Mapping · Remote-Sensing Image Classification
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| Obras citantes distintas | 3 |
|---|---|
| Citações por ano | 0,6 |
| Intervalo de citações | 2021 - 2026 (6) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 3 |