Feature extraction for paper currency recognition

This paper proposes a new technique for paper currency recognition. In this technique, three characteristics of paper currencies including size, color and texture are used in the recognition. By using image histogram, plenitude of different colors in a paper currency is computed and compared with the one in the reference paper currency. The Markov chain concept has been employed to model texture of the paper currencies as a random process. The method proposed in this paper can be used for recognizing paper currencies from different countries. In this method, using only one intact example of paper currency from each denomination is enough for training the system. We tested this method on more than 100 denominations from different countries, and the system was able to recognize 95% of data, correctly.