A Bag of Visual Words Approach for Symbols-Based Coarse-Grained Ancient Coin Classification

Abstract. The field of Numismatics provides the names and descrip-tions of the symbols minted on the ancient coins. Classification of the ancient coins aims at assigning a given coin to its issuer. Various issuers used various symbols for their coins. We propose to use these symbols for a framework that will coarsely classify the ancient coins. Bag of visual words (BoVWs) is a well established visual recognition technique applied to various problems in computer vision like object and scene recognition. Improvements have been made by incorporating the spatial information to this technique. We apply the BoVWs technique to our problem and use three symbols for coarse-grained classification. We use rectangular tiling, log-polar tiling and circular tiling to incorporate spatial informa-tion to BoVWs. Experimental results show that the circular tiling proves superior to the rest of the methods for our problem.