Detection of Counterfeit Indian Currency Note Using Image Processing
Vivek Sharan1, Amandeep Kaur2

1Vivek Sharan, M.Tech Computer Science and Technology, Department of Computer Science and Technology, Central University of Punjab, Bathinda, India.
2Dr. Amandeep Kaur, Associate Professor, Department of Computer Science and Technology, Associate Dean, School of Engineering and Technology, Central University of Punjab, Bathinda, India.
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 2440-2447 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9972109119//2019©BEIESP | DOI: 10.35940/ijeat.A9972.109119
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (

Abstract: Most of the country suffering from the problem of counterfeit note. Indian is also part of such problem. As advance in technology, it is possible for anyone to print counterfeit note. Such counterfeit notes are produced without the legal sanction of Government and production of such notes degrades the economy of any country. After demonetization in India Newly 500 and 2000 currency notes are launched but due to misuse of advanced technology, fake currency of such notes are produced by counterfeiter due to its high value and circulated in most of the part of our country. With the production and circulation of such counterfeit notes, it becomes difficult for common people to differentiate whether the currency is real or fake as they differentiate on the basis of physical appearance which effects the economy of our country. Here a system is proposed to differentiate between real and fake note which is based on the image processing technique and implemented in MATLAB. In this technique, first the image of 500 and 2000 rupee note is captured through the digital camera and perform preprocessing in order to remove noise and then mean intensity of RGB channels of image is calculated and further the three different features including Latent image, RBI Logo and denomination numeral with Rupee symbol are extracted to differentiate between real and fake note. The performance of the proposed system achieves good accuracy rate.
Keywords: Canny Edge, Image Processing, Image Segmentation, Morphological Processing, Mean Intensity.