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Automated Classification of Roman Republican Coins Using Correspondence-Based Method

Explore a large-scale evaluation of automatic coin classification methodology on Roman Republican coins. This study assesses the practicality and accuracy of a top-performing correspondence-based method across a diverse dataset. Results show promising classification accuracy, demonstrating potential in real-world applications for ancient coin classification.

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Automated Classification of Roman Republican Coins Using Correspondence-Based Method

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  1. A Large-Scale Evaluation of Correspondence-Based Coin Classification on Roman Republican Coinage Sebastian Zambanini, Martin Kampel Computer Vision Lab, Vienna University of Technology, Austria {zamba,kampel}@caa.tuwien.ac.at}

  2. Motivation Methodology Results • Ancient coin classification is a challenging task, even for human experts • Support by automatic image-based method • We evaluate the top-performing method of [ZKK14] on a large scale dataset • Goal: investigation of real world practicability • [ZKK14] ZAMBANINI S., KAVELAR A., KAMPEL M.: Classifying ancient coins by local feature matching and pairwise geometric consistency evaluation. In Proc. of ICPR(2014). • Dataset: Rom. Rep. coins, 418 classes, 2 images of obv. & rev. side per class • Correct class is under top 5 classes in 93.5% of the cases Exemplar images Compare Low inter-classvariation Class ID High intra-classvariation Titel Intra-class variations: non-rigid deformations

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