The developing nations like India facing many fake currency issues, these are always created a problem in international markets. The increasing advancements in technology there is a possibility of generating a fake counterfeit. If this currency circulated in the markets, then automatically the GDP and economy of the country automatically reduce. Many accurate counting and scanning machines are available in banks, markets and commercial areas, but these are detected the fake currency with less accuracy. Therefore fake currency arises into global marketing and affects the common people. The above limitations are developed with image processing techniques with machine learning models. In this research work, image acquisition and “enhanced support vector machine (ESVM)” classification is applied on selected currency note images. The performance measures such as accuracy, efficiency, recall are estimated and compared with existed methods. The simulated results outperform the present techniques and challenging the current technologies.
Volume 12 | Issue 6
Pages: 170-179
DOI: 10.5373/JARDCS/V12I6/S20201018