Abstract
Recognizing the type of an ancient coin requires theoretical expertise and years of experience in the field of numismatics. Our goal in this work is automatizing thistime-consuming and demanding task by a visual classification framework.

Specifically, we propose to model ancient coin image classification using Graph Transduction Games (GTG). GTG casts the classification problem as a non-cooperative game wherethe players (the coin images) decide their strategies (class labels) according to the choices made by the others, which results with a global consensus at the final labeling.Experiments are conducted on the only publicly available dataset which is composed of 180 images of 60 types of Roman coins. We demonstrate that our approach outperforms theliterature work on the same dataset with the classification accuracy of 73.6% and 87.3% when there are one and two images per class in the training set, respectively.

Ancient coins, that depict cultural, political and military events, natural phenomena, ideologies and portraits of god and emperors are important source of information forhistorians and archaeologists. Recognizing the type of an ancient coin requires theoretical expertise and years of experience in the field of numismatics. A common way to detectthe period of a discovered coin is searching through the manual books where ancient coins are indexed which requires a highly time consuming labor.

Our goal in this paper is automatizing recognition of Roman coins by employing computer vision and pattern recognition techniques. Automatizing such a manual procedure not onlyprovides faster processing time but also can support historians and archaeologists for a more accurate decision. A visual classification framework for ancient coin recognition canalso be used at museums or by individual collectors to organize large collections of coins.

From the computer vision point of view, classification of ancient coin images is a highly challenging task. One of the difficulties arises from existence of high number oftypes (i.e. classes) in ancient coins (e.g. Portuguese coins from medieval period and coins from Roman Republic compose over 1500 and 550 different classes, respectively), whilemost of the classes include few known specimens as mentioned... Moreover, intra-class variation is large due to local spatial variations arising from missing parts anddegradations on the coins, and manual manufacturing of coins by different engravers. Another reason of large intra-class variation is the metallic structure of these coins yieldsto strong reflection and shading variations so the appearance of the same coin changes significantly under different lighting conditions.

To read the complete article, see:
Ancient Coin Classification Using Graph Transduction Games (https://arxiv.org/pdf/1810.01091.pdf)