Ritz, Martin ; Santos, Pedro ; Fellner, Dieter W. (2022)
Automated Classification of Crests on Pottery Sherds Using Pattern Recognition on 2D Images.
20th Eurographics Workshop on Graphics and Cultural Heritage (GCH 2022). Delft, The Netherlands (28.-30.09.2022)
doi: 10.2312/gch.20221235
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Manual classification of artefacts is a labor intensive process. Based on 2D images and 3D scans of - for example - ceramic shards, we developed a pattern recognition algorithm which automatically extracts relief features for each newly recorded object and tries to automate the classification process. Based on characteristics found, previously unknown objects are automatically corelated to already classified objects of a collection exhibiting the greatest similarity. As a result, classes of artefacts form iteratively, which ultimately also corresponds to the overall goal which is the automated classification of entire collections. The greatest challenge in developing our software approach was the heterogeneity of reliefs, and in particular the fact that current machine learning approaches were out of question due to the very limited number of objects per class. This led to the implementation of an analytical approach that is capable of performing a classification based on very few artefacts.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Ritz, Martin ; Santos, Pedro ; Fellner, Dieter W. |
| Art des Eintrags: | Bibliographie |
| Titel: | Automated Classification of Crests on Pottery Sherds Using Pattern Recognition on 2D Images |
| Sprache: | Englisch |
| Publikationsjahr: | 12 Januar 2022 |
| Verlag: | Eurographics Association |
| Buchtitel: | Eurographics Workshop on Graphics and Cultural Heritage |
| Reihe: | GCH |
| Veranstaltungstitel: | 20th Eurographics Workshop on Graphics and Cultural Heritage (GCH 2022) |
| Veranstaltungsort: | Delft, The Netherlands |
| Veranstaltungsdatum: | 28.-30.09.2022 |
| DOI: | 10.2312/gch.20221235 |
| Kurzbeschreibung (Abstract): | Manual classification of artefacts is a labor intensive process. Based on 2D images and 3D scans of - for example - ceramic shards, we developed a pattern recognition algorithm which automatically extracts relief features for each newly recorded object and tries to automate the classification process. Based on characteristics found, previously unknown objects are automatically corelated to already classified objects of a collection exhibiting the greatest similarity. As a result, classes of artefacts form iteratively, which ultimately also corresponds to the overall goal which is the automated classification of entire collections. The greatest challenge in developing our software approach was the heterogeneity of reliefs, and in particular the fact that current machine learning approaches were out of question due to the very limited number of objects per class. This led to the implementation of an analytical approach that is capable of performing a classification based on very few artefacts. |
| Freie Schlagworte: | Image processing, Pattern recognition, Visual computing |
| Zusätzliche Informationen: | GCH 2022 - Eurographics Workshop on Graphics and Cultural Heritage |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 16 Jan 2023 10:22 |
| Letzte Änderung: | 16 Jan 2023 10:22 |
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