Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W2, 373-378, 2013
https://doi.org/10.5194/isprsarchives-XL-5-W2-373-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
22 Jul 2013
THE ILAC-PROJECT: SUPPORTING ANCIENT COIN CLASSIFICATION BY MEANS OF IMAGE ANALYSIS
A. Kavelar1, S. Zambanini1, M. Kampel1, K. Vondrovec2, and K. Siegl2 1Computer Vision Lab, Vienna University of Technology, Favoritenstr. 9/183-2, 1040 Vienna, Austria
2Coin Cabinet, Museum of Fine Arts, Burgring 5, 1010 Vienna, Austria
Keywords: Ancient coins, computer vision, numismatics, optical character recognition, image matching 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.
Conference paper (PDF, 3036 KB)


Citation: Kavelar, A., Zambanini, S., Kampel, M., Vondrovec, K., and Siegl, K.: THE ILAC-PROJECT: SUPPORTING ANCIENT COIN CLASSIFICATION BY MEANS OF IMAGE ANALYSIS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W2, 373-378, https://doi.org/10.5194/isprsarchives-XL-5-W2-373-2013, 2013.

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