Fake Currency Detection using Clustering and SVM Classification

Authors(2) :-Achal Kamble, Prof. Mrudula Nimbarte

Coins and note currency are widely used in our daily life such as vending machines, parking meters, telephone booths and so on. In addition to being used as currency, people enjoy collecting coins and notes as they usually have artistic value and can give a vivid insight to the social life in history. However, in recent years, a lot of illegal counterfeiting rings manufacture and sell fake coins and at the same time fake note currency is printed as well, which have caused great loss and damage to the society. Thus it is imperative to be able to detect fake currency. We propose a new approach to detect fake Indian notes using their images. A currency image is represented in the dissimilarity space, which is a vector space constructed by comparing the image with a set of prototypes. Each dimension measures the dissimilarity between the image under consideration and a prototype. In order to obtain the dissimilarity between two coin images, the local key points on each image are detected and described. Based on the characteristics of the coin, the matched key points between the two images can be identified in an efficient manner. A post processing procedure is further proposed to remove mismatched key points. Due to the limited number of fake currency in real life, one-class learning is conducted for fake currency detection, so only genuine currency are needed to train the classifier.

Authors and Affiliations

Achal Kamble
Department of Computer Engineering Bapurao Deskmukh College of Engineering Wardha, Maharashtra, India
Prof. Mrudula Nimbarte
Department of Computer Engineering Bapurao Deskmukh College of Engineering Wardha, Maharashtra, India

Fake currency, fake currency detection, currency image representation, dissimilarity space, class learning.

  1. Li Liu, Yue Lu "An Image-Based Approach to Detection of Fake Coins" in IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY June 2017.
  2. A Roy "Machine-assisted authentication of paper currency: an experiment on Indian banknotes "International Journal on Document Analysis and Recognition, 18(3): 271-285, 2015.
  3. Sun.Ke, "Detection of Counterfeit Coins and Assessment of Coin Qualities" IEEE Conference 2015.
  4. L. Liu "Variable-length signature for near-duplicate image matching " IEEE Conference 2015.
  5. Jongpil Kim "Ancient Coin Recognition Based on Spatial Coding" IEEE Conference 2015.
  6. R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd ed., Prentice Hall India, ISBN- 81-203-2758-6, 2006.M. Young, The Technical Writer’s Handbook. Mill Valley, CA: University Science, 1989.
  7. Ms.Rumi Ghosh, Mr Rakesh Khare, "A Study on Diverse Recognition Techniques for Indian Currency Note" ,IJESRT, Vol.2, Issue 6, June 2013.R. Nicole, "Title of paper with only first word capitalized," J. Name Stand. Abbrev., in press.
  8. Amol A. Shirsath S. D. Bharkad, "Survey of Currency Recognition System Using Image Processing", IJCER, Vol.3, Issue 7, pp 36-40, July 2013.
  9. M.Deborah and Soniya Prathap "Detection of Fake currency using Image Processing". IJISET- International Journal of Innovative Science, Engineering & Technology, Vol. 1, Issue 10, 2014.
  10. Faiz M. Hasanuzzaman, Xiaodong Yang, and YingLi Tian, Senior Member, IEEE Robust and Effective Component-based Banknote Recognition for the Blind IEEE Trans Syst Man Cybern C Appl Rev. 2012 Nov; 42(6): 1021–1030.
  11. Mohammad H Alshayeji, Mohammad Al-Rousan and Dunya T. Hassoun, Detection Method for Counterfeit Currency Based on Bit-Plane Slicing Technique ,International Journal of Multimedia and Ubiquitous Engineering Vol.10, No.11 (2015).
  12. Nayana Susan Jose, Shermin Siby, Juby Mathew, Mrudula Das ,Android Based Currency Recognition System for Blind, International Journal of Engineering Research in Computer Science and Engineering (IJERCSE) Vol 2, Issue 4, April 2015
  13. Rubeena Mirza, Vinti Nanda, Characteristic Extraction Parameters for Genuine Paper Currency Verification Based on Image Processing, IFRSA International Journal of Computing, Volume 2, Issue 2, April 2012.
  14. Komal Vora, Ami Shah, Jay Mehta, A Review Paper on Currency Recognition System, InternationalJournal of Computer Applications (0975-8887) Volume 115-No. 20, April 2015.
  15. G. Trupti Pathrabe, Mrs.Swapnili Karmore, A Novel Approach of Embedded System for Indian Paper Currency Recognition, International Journal of Computer Trends and Technology, May to June Issue 2011, ISSN: 2231-2803
  16. Pathrabe T, Bawane N.G, Feature Extraction Parameters for Genuine Paper Currency Recognition & Verification, International Journal of Advanced Engineering Sciences and Technologies, Volume 2, 85- 89, 2011.
  17. B.Sai Prasanthi, D. Rajesh Setty , Indian Paper Currency Authentication System using Image processing International Journal of Scientific Research Engineering & Technology (IJSRET), ISSN 2278-0882.
  18. S. Surya, G. Thailambal , Comparative Study on Currency Recognition System Using Image Processing , International Journal Of Engineering And Computer Science ISSN:2319-7242.
  19. Chinmay Bhurke, Meghana Sirdeshmukh, M.S.Kanitkar, Currency Recognition Using Image Processing , International Journal of Innovative Research in Computer and Communication Engineering (An ISO 3297: 2007 Certified Organization) Vol. 3, Issue 5, May 2015.

Publication Details

Published in : Volume 3 | Issue 4 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 155-161
Manuscript Number : CSEIT1833190
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Achal Kamble, Prof. Mrudula Nimbarte, "Fake Currency Detection using Clustering and SVM Classification", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 4, pp.155-161, March-April.2018
URL : http://ijsrcseit.com/CSEIT1833190

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