Since money exchange is important in our daily life, many types of equipments such as Vending Machines, Currency Sorters, Automatic Teller Machines (ATM) and Currency Recognition systems for blind people have been made. More advanced devices with more capabilities are being made each day. As a result, efficient, fast and reliable currency recognition methods are required. Most currency recognition methods only use one attribute of currency images, such as major color, Ultra Violet spectrum or texture that are extracted from currency images. In this paper, we introduce a method for currency recognition that combines texture and color data together and applies them to a neural network. The best result from the other existing methods is at most 85 percent but our method shows 10 percent improvement compared to existing solutions.