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The document and banknote counterfeiting remove us as a usurpation of the rights of individuals and institutions. By the advancement of technology special paper, the ink usage in the original banknote, placing watermarks, micro text are challenged to fraud that also does not prevent the counterfeiting of widespread. The counterfeit banknotes detection and minimizing damage is one of the important elements. In this, decided and expert systems can be improved to estimate the counterfeit banknotes to using dates of the moneys. The data of banknotes are sorted before to this point, after comparative results are discussed of the testing. In this study, it is classified by the classification algorithms to using digitized available data of real and counterfeit banknotes images. Artificial Neural Networks and Support Vector Machines are used in the classification. Correctly identified is detected to rate of 74.6% in the test results which is tested by Artificial Neural Networks, correctly identified is detected to rate of 93.8% in the results of tests which is tested by Support Vector Machines. |
