• Corpus ID: 212482262

Currency Verification System Based on Characteristic Extraction Using Image Processing

  title={Currency Verification System Based on Characteristic Extraction Using Image Processing},
  author={Rubeena Mirza and Vinti Nanda},
68  Abstract— Over the past 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 paper currency, 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 distinguishing counterfeit banknotes from genuine ones… 

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  • 2006
Michiyuk ―Recognition of Paper Currencies by Hybrid Neural Network
  • IEEE Transactions on Neural Networks‖,
  • 1998
Reswan Hakkim -Extraction of License Plate Region in Automatic License Plate Recognition‖
  • International Conference on Mechanical and Electrical Technology, IEEE Transactions
Digital Image Processing (Third Edition), Pearson Education, New Delhi, 110092
  • Chhattisgarh in 2006 and M.Tech in Computer Science & Engineering from Rungta College of Engineering
  • 2008