Fake Currency Detection Using Image Processing

  • Authors

    • Ankur Saxena
    • Pawan Kumar Singh
    • Ganesh Prasad Pal
    • Ravi Kumar Tewari
    2018-12-13
    https://doi.org/10.14419/ijet.v7i4.39.23931
  • Digital Image Processing, Dilation, Grayscale, Image classification, linear correlation.
  • Since last few years, as a result of the great technological advances in color printing, duplicating and scanning, counterfeiting problems have become more and more serious. In the past, only the printing house has the ability to make counterfeit note, but today it is possible for any person to print counterfeit bank notes simply by using a computer and a laser printer at house. Therefore the issue of efficiently verifying counterfeit banknotes from real ones via automatic machines has become more and more important. Counterfeit notes are a problem of almost every country but India has been hit really hard and has become a very acute problem. There is a need to design a system that will helpful for recognition of paper currency notes with fast speed and in less time. This proposed system describes an approach for verification of Indian banknotes. The currency will be checked out by using image processing techniques. The approach consists of a number of elements including processing of image, detection of edge, image segmentation, drawing out characteristic, comparing both images. The image processing approach is discussed with MATLAB to verify the parameters of note. Image processing involves changing the nature of an image in order to improve its visual information for human interpretation. The image processing software is a collection of functions that extends the capability of the MATLAB numeric computing environment. The result will be whether note is real or fake.

     

     

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  • How to Cite

    Saxena, A., Kumar Singh, P., Prasad Pal, G., & Kumar Tewari, R. (2018). Fake Currency Detection Using Image Processing. International Journal of Engineering & Technology, 7(4.39), 199-205. https://doi.org/10.14419/ijet.v7i4.39.23931