Automated Classification of Crests on Pottery Sherds Using Pattern Recognition on 2D Images
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
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.
Description
CCS Concepts: Computing methodologies --> Image processing; Applied computing --> Archaeology
@inproceedings{10.2312:gch.20221235,
booktitle = {Eurographics Workshop on Graphics and Cultural Heritage},
editor = {Ponchio, Federico and Pintus, Ruggero},
title = {{Automated Classification of Crests on Pottery Sherds Using Pattern Recognition on 2D Images}},
author = {Ritz, Martin and Santos, Pedro and Fellner, Dieter W.},
year = {2022},
publisher = {The Eurographics Association},
ISSN = {2312-6124},
ISBN = {978-3-03868-178-6},
DOI = {10.2312/gch.20221235}
}