An Intelligent Method for Indian Counterfeit Paper Currency Detection - Diana Andrushia; Mary Neebha; Thusnavis Bella Mary (Journal of Information Technology Management)
The production of counterfeit paper currencies has become cheaper because of the advancement in the printing technologies. The circulation of counterfeit currencies down the economy of a country. By leveraging this, there is a mandate to develop an intelligent technique for the detection and classification of counterfeit currencies. The intelligent techniques play a major role in the field of Human Computer Interaction (HCI) too. This paper deals with the detection of counterfeit Indian currencies. The proposed method feature extraction is based on the characteristics of Indian paper currencies. The first order and second order statistical features are extracted initially from the input. The effective feature vectors are given to the SVM classifier unit for classification. The proposed method produced classification accuracy of 95.8%. The experimental results are compared with state-of-the methods and produced reliable results.