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Fake Currency Detection Using Machine Learning and Image Processing

Chinchudev L V, Dr. Neethu Sathyan

Abstract


The paper addresses the issue of determining whether the given sample of currency is fake. Based on the colors, width, and se- rial numbers indicated, various conventional techniques and ap- proaches are available for identifying fake currency. Various ma- chine learning techniques are proposed by image processing in the advanced period of computer science and high computing ap- proaches, which provides 99.9% accuracy for the fake identifica- tion of the currency. Methods for detection and recognition that go beyond algorithms include entities like color, shape, paper width, and note image filtering. This paper suggests utilising K-Nearest Neighbours, followed by image processing, to identify counter- feit money. The banknote authentication dataset used in this was developed using advanced computational and mathematical tech- niques, providing accurate data and information about the entities and properties related to the currency. Machine learning algorithms and image processing are used in data processing and data extrac- tion to obtain the desired outcome and accuracy.


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