The ability to recognize the value of different forms of currency is a necessary skill in the everyday life of most human beings. In order to automate monetary transactions, it is necessary to enable computers to perform such recognition as well. Towards this end, we created a system that could correctly identify coins. As a means of limiting the scope of this problem, our project focused on recognizing the tail side of standard US coins in a specific orientation. More specifically, the system was designed to differentiate between the bald eagle on the quarter, the torch of liberty on the dime, Thomas Jefferson's house on the nickel, and the Lincoln Memorial on the penny. Our system focuses on recognizing the texture of these imprinted images rather than the use of other features, such as coin color. Furthermore, the image size of each coin was normalized to prevent size dependent classification. The system resulting from our research recognizes single coins using vector quantization and histogram modeling with a 94% success rate on our test data.