A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies
Cultural heritage images are among the primary media for communicating and preserving the cultural values of a society. The images represent concrete and abstract content and symbolise the social, economic, political, and cultural values of the society. However, an enormous amount of such values emb...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Journal of Imaging |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-433X/7/8/121 |
| _version_ | 1797523368264597504 |
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| author | Yalemisew Abgaz Renato Rocha Souza Japesh Methuku Gerda Koch Amelie Dorn |
| author_facet | Yalemisew Abgaz Renato Rocha Souza Japesh Methuku Gerda Koch Amelie Dorn |
| author_sort | Yalemisew Abgaz |
| collection | DOAJ |
| description | Cultural heritage images are among the primary media for communicating and preserving the cultural values of a society. The images represent concrete and abstract content and symbolise the social, economic, political, and cultural values of the society. However, an enormous amount of such values embedded in the images is left unexploited partly due to the absence of methodological and technical solutions to capture, represent, and exploit the latent information. With the emergence of new technologies and availability of cultural heritage images in digital formats, the methodology followed to semantically enrich and utilise such resources become a vital factor in supporting users need. This paper presents a methodology proposed to unearth the cultural information communicated via cultural digital images by applying Artificial Intelligence (AI) technologies (such as Computer Vision (CV) and semantic web technologies). To this end, the paper presents a methodology that enables efficient analysis and enrichment of a large collection of cultural images covering all the major phases and tasks. The proposed method is applied and tested using a case study on cultural image collections from the Europeana platform. The paper further presents the analysis of the case study, the challenges, the lessons learned, and promising future research areas on the topic. |
| first_indexed | 2024-03-10T08:41:58Z |
| format | Article |
| id | doaj.art-6d66aef675954d7b84a1a78e2624930a |
| institution | Directory Open Access Journal |
| issn | 2313-433X |
| language | English |
| last_indexed | 2024-03-10T08:41:58Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Imaging |
| spelling | doaj.art-6d66aef675954d7b84a1a78e2624930a2023-11-22T08:13:41ZengMDPI AGJournal of Imaging2313-433X2021-07-017812110.3390/jimaging7080121A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence TechnologiesYalemisew Abgaz0Renato Rocha Souza1Japesh Methuku2Gerda Koch3Amelie Dorn4ADAPT Centre, School of Computing, Dublin City University, Glasnevin Campus, Dublin 9, Dublin, IrelandAustrian Centre for Digital Humanities and Cultural Heritage (ACDH-CH OeAW), Austrian Academy of Sciences, 1010 Vienna, AustriaADAPT Centre, School of Computing, Dublin City University, Glasnevin Campus, Dublin 9, Dublin, IrelandAIT Angewandte Informationstechnik Forschungsgesellschaft mbH, Europeana Local AT, Klosterwiesgasse 32, 8010 Graz, AustriaAustrian Centre for Digital Humanities and Cultural Heritage (ACDH-CH OeAW), Austrian Academy of Sciences, 1010 Vienna, AustriaCultural heritage images are among the primary media for communicating and preserving the cultural values of a society. The images represent concrete and abstract content and symbolise the social, economic, political, and cultural values of the society. However, an enormous amount of such values embedded in the images is left unexploited partly due to the absence of methodological and technical solutions to capture, represent, and exploit the latent information. With the emergence of new technologies and availability of cultural heritage images in digital formats, the methodology followed to semantically enrich and utilise such resources become a vital factor in supporting users need. This paper presents a methodology proposed to unearth the cultural information communicated via cultural digital images by applying Artificial Intelligence (AI) technologies (such as Computer Vision (CV) and semantic web technologies). To this end, the paper presents a methodology that enables efficient analysis and enrichment of a large collection of cultural images covering all the major phases and tasks. The proposed method is applied and tested using a case study on cultural image collections from the Europeana platform. The paper further presents the analysis of the case study, the challenges, the lessons learned, and promising future research areas on the topic.https://www.mdpi.com/2313-433X/7/8/121cultural imagescultural heritageartificial intelligencecomputer visionsemantic enrichmentimage analysis |
| spellingShingle | Yalemisew Abgaz Renato Rocha Souza Japesh Methuku Gerda Koch Amelie Dorn A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies Journal of Imaging cultural images cultural heritage artificial intelligence computer vision semantic enrichment image analysis |
| title | A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies |
| title_full | A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies |
| title_fullStr | A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies |
| title_full_unstemmed | A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies |
| title_short | A Methodology for Semantic Enrichment of Cultural Heritage Images Using Artificial Intelligence Technologies |
| title_sort | methodology for semantic enrichment of cultural heritage images using artificial intelligence technologies |
| topic | cultural images cultural heritage artificial intelligence computer vision semantic enrichment image analysis |
| url | https://www.mdpi.com/2313-433X/7/8/121 |
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