Using Hidden Markov Models for Feature Extraction in Paper Currency Recognition
نویسنده
چکیده
This paper proposes a new feature extraction technique for paper currency recognition. In this technique, the texture characteristic is used in the recognition. The Markov chain concept has been employed to model the texture of 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 only intact examples of paper currencies from each denomination are used 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.
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