publication . Article . Other literature type . 2018


Albert Kavelar; Sebastian Zambanini; Martin Kampel; Klaus Vondrovec; Kathrin Siegl;
Open Access
  • Published: 15 Jan 2018 Journal: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, volume XL-5/W2, pages 373-378 (eissn: 2194-9034, Copyright policy)
  • Publisher: Copernicus GmbH
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.
free text keywords: Numismatics, Optical character recognition, computer.software_genre, computer, Computer vision, Process (computing), Symbol (chemistry), Image (mathematics), Engineering, business.industry, business, Image matching, Information retrieval, Exploit, Upload, Artificial intelligence, lcsh:Technology, lcsh:T, lcsh:Engineering (General). Civil engineering (General), lcsh:TA1-2040, lcsh:Applied optics. Photonics, lcsh:TA1501-1820
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