Reliable object identification is an essential task in the process of recognition and traceability of stolen cultural heritage. Existing approaches for object recognition focus mainly on object classification. However, they are not sufficient to identify a given object among hundreds of objects of the same class. In this paper, we investigate the feasibility of computer aided identification of ancient coins. Since the shape of a coin is a very unique feature, we first apply a shape descriptor to capture its characteristics. In the next step, local features are used to describe the die information. We present experiments on a data set of 2400 images of ancient coins. The evaluation results show that our approach is competitive. Moreover, it indicates some outstanding features that show great promise for reliable object identification in the area of cultural heritage. © 2008 Springer Berlin Heidelberg.
CITATION STYLE
Huber-Mörk, R., Zaharieva, M., & Czedik-Eysenberg, H. (2008). Numismatic object identification using fusion of shape and local descriptors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5359 LNCS, pp. 368–379). https://doi.org/10.1007/978-3-540-89646-3_36
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