Objective of the project work: Detecting counterfeit banknotes through image processing contributes to overall financial security. Ensure swift detection and response to counterfeit threats, minimizing the time between detection and action. Automate the detection process for enhanced efficiency, reducing dependence on manual inspection. The proposed system aims to tackle the issue of counterfeit Indian currency notes, particularly focusing on 500-rupee denominations, using Python and OpenCV for image processing tasks.
Methodology: Python, coupled with OpenCV, provides the computational tools necessary for processing these currency images on a computer. Through a series of image processing steps such as edge detection, grayscale conversion, and feature extraction using algorithms like SSIM and ORB, the system aims to accurately differentiate between real and fake currency notes. Feedback is provided by the system through clear messages regarding the authenticity of the currency note enables swift action to be taken by authorities, thereby strengthening overall fraud prevention efforts.