Robust Automatic Segmentation of Ancient Coins

Nowadays, ancient coins are becoming subject to a very large illicit trade. Thus, the interest in reliable automatic coin recognition systems within cultural heritage and law enforcement institutions rises rapidly. Central component in the permanent identification and traceability of coins is the underlying image recognition technology. Prior to any analysis a coin image has to be segmented into two areas: the area depicting the coin and the area belonging to the background. In this paper, we focus on the segmentation task as a preprocessing step for any automated coin recognition system. The objective is a robust segmentation procedure for a large variety of coin image styles. We present a simple and fast method for coin segmentation, based on local entropy and gray value range. Results of the developed algorithm are shown for an image database of ancient coins and demonstrate the benefits of our approach.