The creation and circulation of counterfeit notes are on the rise right now, as a result of advances in color printing technology. This is a serious issue that affects practically all of the nations. The economy is impacted. Such fake money fuels evil intentions, typically involving terrorist actions. According to the research, this has had a highly negative effect on developing nations like India. This research suggests a method for viewing the fake currency through its image. Pre-processing should be used after choosing an image. Then a conversion from RGB to GRAYSCALE is done. Banks and other trading places have equipment available to verify financial validity. Nevertheless, the normal individual does not have access to such tools, which is why fake money detecting software that is usable by regular people is required. We get at most 81% of accuracy considering 50 items of Indian Currency notes of 500-rupee. This project provides a thorough explanation of a fake note detector that can be used by the average person. The suggested system employs image processing to identify genuine currency from counterfeit money. The Python programming language has been used to create the software in its entirety.
Fake Currency, Image Processing, Grayscale Conversion, Segmentation, pre-processing
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