Nondestructive characterization and artificial intelligence recognition of acoustic identifiers of ancient ceramics
Abstract Cultural heritage identity management is the most basic and important work in the process of cultural heritage protection. It is of great significance to provide a unique and identifiable digital identity for ancient ceramics. At present, the identification information of ancient ceramics i...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-07-01
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| Series: | Heritage Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40494-023-00990-9 |
| _version_ | 1797778772801355776 |
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| author | Xiaoxue Jin Xiufeng Wang Chaohua Xue |
| author_facet | Xiaoxue Jin Xiufeng Wang Chaohua Xue |
| author_sort | Xiaoxue Jin |
| collection | DOAJ |
| description | Abstract Cultural heritage identity management is the most basic and important work in the process of cultural heritage protection. It is of great significance to provide a unique and identifiable digital identity for ancient ceramics. At present, the identification information of ancient ceramics is mainly composed of external visual characteristics, and there is no report on feature identification method that can reflect the properties of ancient ceramics. Audible sound signals not only have advantages in non-destructive testing, but also can be used as voiceprint information to identify, monitor and analyze ancient ceramics. In this paper, seven ancient ceramics and 12 similar modern ceramic cups are taken as research objects, and an acoustic identifier (AID) is constructed. We put forward a reliable acoustic identification method for ancient ceramics, and established a digital code of acoustic characteristics of ancient ceramics. The results show that audible sound waves can reflect the attribute information of ancient ceramics. Sufficient acoustic data combined with deep learning can not only accurately match the identity of ancient ceramics, but also detect the real-time identity information of ancient ceramics, and make a comparative analysis of its cracks and whether it has caused damage. This method can provide a variety of practical applications for audible signal feature recognition technology in the exhibition, protection, trading, recognition and safety management of ancient ceramics and other cultural relics. |
| first_indexed | 2024-03-12T23:21:25Z |
| format | Article |
| id | doaj.art-81e4d93e115f440b8c3a1e8b4c7bd44e |
| institution | Directory Open Access Journal |
| issn | 2050-7445 |
| language | English |
| last_indexed | 2024-03-12T23:21:25Z |
| publishDate | 2023-07-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Heritage Science |
| spelling | doaj.art-81e4d93e115f440b8c3a1e8b4c7bd44e2023-07-16T11:24:32ZengSpringerOpenHeritage Science2050-74452023-07-0111111010.1186/s40494-023-00990-9Nondestructive characterization and artificial intelligence recognition of acoustic identifiers of ancient ceramicsXiaoxue Jin0Xiufeng Wang1Chaohua Xue2Key Laboratory of Materials and Technology for Underground Cultural Relics Protection, Ministry of Education, Shaanxi University of Science and TechnologyKey Laboratory of Materials and Technology for Underground Cultural Relics Protection, Ministry of Education, Shaanxi University of Science and TechnologySchool of Bioresources Chemical and Materials Engineering, Shaanxi University of Science and TechnologyAbstract Cultural heritage identity management is the most basic and important work in the process of cultural heritage protection. It is of great significance to provide a unique and identifiable digital identity for ancient ceramics. At present, the identification information of ancient ceramics is mainly composed of external visual characteristics, and there is no report on feature identification method that can reflect the properties of ancient ceramics. Audible sound signals not only have advantages in non-destructive testing, but also can be used as voiceprint information to identify, monitor and analyze ancient ceramics. In this paper, seven ancient ceramics and 12 similar modern ceramic cups are taken as research objects, and an acoustic identifier (AID) is constructed. We put forward a reliable acoustic identification method for ancient ceramics, and established a digital code of acoustic characteristics of ancient ceramics. The results show that audible sound waves can reflect the attribute information of ancient ceramics. Sufficient acoustic data combined with deep learning can not only accurately match the identity of ancient ceramics, but also detect the real-time identity information of ancient ceramics, and make a comparative analysis of its cracks and whether it has caused damage. This method can provide a variety of practical applications for audible signal feature recognition technology in the exhibition, protection, trading, recognition and safety management of ancient ceramics and other cultural relics.https://doi.org/10.1186/s40494-023-00990-9Ancient ceramicsAcoustic identifierNon-destructive testingDeep learningHeritage management |
| spellingShingle | Xiaoxue Jin Xiufeng Wang Chaohua Xue Nondestructive characterization and artificial intelligence recognition of acoustic identifiers of ancient ceramics Heritage Science Ancient ceramics Acoustic identifier Non-destructive testing Deep learning Heritage management |
| title | Nondestructive characterization and artificial intelligence recognition of acoustic identifiers of ancient ceramics |
| title_full | Nondestructive characterization and artificial intelligence recognition of acoustic identifiers of ancient ceramics |
| title_fullStr | Nondestructive characterization and artificial intelligence recognition of acoustic identifiers of ancient ceramics |
| title_full_unstemmed | Nondestructive characterization and artificial intelligence recognition of acoustic identifiers of ancient ceramics |
| title_short | Nondestructive characterization and artificial intelligence recognition of acoustic identifiers of ancient ceramics |
| title_sort | nondestructive characterization and artificial intelligence recognition of acoustic identifiers of ancient ceramics |
| topic | Ancient ceramics Acoustic identifier Non-destructive testing Deep learning Heritage management |
| url | https://doi.org/10.1186/s40494-023-00990-9 |
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