The Ilac-Project: Supporting Ancient Coin Classification by Means of Image Analysis

Abstract

ABSTRACT:This paper presents the ILAC project, which aims at the development of an automated image-based classification system for ancient Roman Republican coins. The benefits of such a system are manifold: operating at the suture between computer vision and numismatics, ILAC can reduce the day-to-day workload of numismatists by assisting them in classification tasks and providing a preselection of suitable coin classes. This is especially helpful for large coin hoard findings comprising several thousands of coins. Furthermore, this system could be implemented in an online platform for hobby numismatists, allowing them to access background information about their coin collection by simply uploading a photo of obverse and reverse for the coin of interest. ILAC explores different computer vision techniques and their combinations for the use of image-based coin recognition. Some of these methods, such as image matching, use the entire coin image in the classification process, while symbol or legend recognition exploit certain characteristics of the coin imagery. An overview of the methods explored so far and the respective experiments is given as well as an outlook on the next steps of the project.

Ancient Coin Classification Using Reverse Motif Recognition: Image-based classification of Roman Republican coins

“…the Art expert'S opinion on the AchieVed reSultS Given the fundamental task of the already closed project [28], a rate of 80% accurate results proves that it is possible to gain a real benefit from the developed algorithms. Of course, to push this rate to 98 or 99%, a multiple amount of reference images and probably more "fine-tuning" (e.g., their proper selection based on the degree of preservation) would be required.…”

Deep Ancient Roman Republican Coin Classification via Feature Fusion and Attention

“…comprises about 3900 coins. The ILAC project [30] collected the image dataset of these coins with a uniform background. However, there exist orientation differences between the coin images as they are not photographed under their canonical orientations based on their central reverse motifs.…”

Image analysis and deep learning for aiding professional coin grading

“…With the development of computer vision and artificial intelligence, image-based coin type identification approaches have been investigated for the recent decade [2,3,4,5]. However, image-based coin grading remains an issue to explore.…”