• Corpus ID: 41690405

A Survey on Counterfeit Paper Currency Recognition and Detection

  title={A Survey on Counterfeit Paper Currency Recognition and Detection},
  author={Shital M. Mahajan and K. P. Rane},
This surveys paper reports various articles dealing with counterfeit paper currency recognition and detection systems. This paper attempts to represent the survey on fake money detection because almost every country in the world is facing the problem of forged money, but in India, the problem is exasperating as the country is hit hard by this evil practices. Counterfeit notes of Rs.100, 500 and 1000 are being spread all over the world that’s why it is important to detect such fake notes which… 
Detection of Fake Indian Currency
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Techniques used in each of the four areas recognize banknote information (denomination, serial number, authenticity, and physical condition) based on image or sensor data, and are actually applied to banknote processing machines across the world.
Image processing based Feature extraction of Bangladeshi banknotes
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  • Computer Science
    The 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2014)
  • 2014
A core software system to build a robust automated counterfeit currency detection tool for Bangladeshi bank notes using OCR, Contour Analysis, Face Recognition, Speeded UP Robust Features (SURF) and Canny Edge & Hough transformation algorithm of OpenCV is presented.
Identity Document and banknote security forensics: a survey
The present survey covers a wide range of anti-counterfeiting security features, categorizing them into three components: security substrate, security inks and security printing respectively, and presents works in the literature covering these three categories.
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The proposed method feature extraction is based on the characteristics of Indian paper currencies and produced classification accuracy of 95.8%.
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Bogus currency authorization using HSV techniques
The main objective of this work is used to identify fake currencies among the real currency by using edge detection techniques, used to enhance reliability and dynamic way in detecting the counterfeit currency.
Fig . 3 Output Image III . PROPOSED WORK FLOW CHART : Fig . 4 Block diagram ALGORITHM : STEP 1
In the proposed work, detection of the counterfeit banknotes using multispectral images is implemented by Neural Network technique, which will reduce the cost when neural networks are used and shows good performance and a low level of complexity.
A computer vision based approach for Indian paper currency detection by using ORB and BF matcher in OpenCV based and the average accuracy of detection is up to 95.0% and tested this method on different denominations of Indian banknote.


An Automated Recognition of Fake or Destroyed Indian Currency Notes in Machine Vision
An automa ed recognition of currency notes is introduced by with the help of feature extraction, classification based in SVM, Neural Net s, and heuristic approach to deal with fake notes in India.
Research on identification the counterfeit by recognizing the infrared images
In this paper, the original infrared images have been embossed process firstly, then the binary images are gained by using closing operation, and the template matching is used to identify.
Feature extraction for paper currency recognition
In this method, using only one intact example of paper currency from each denomination is enough for training the system, and the system was able to recognize 95% of data, correctly.
Bangladeshi banknote recognition by neural network with axis symmetrical masks
  • N. Jahangir, A. Chowdhury
  • Computer Science
    2007 10th international conference on computer and information technology
  • 2007
Experimental results show that this Neural Network based recognition scheme for Bangladeshi banknotes can recognize currently available 8 notes successfully with an average accuracy of 98.57%.
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A method using linear transform of image gray to diminish the influence of the background image noises in order to give prominence to edge information of the image is put forward.
A Digit Recognition System for Paper Currency Identification based on Virtual Machines
The approach consists of a number of components including image preprocessing, image binarisation, morphological filtering, segmentation, feature extraction and digit recognition, which shows that it is effective and efficient and can clearly meet the system requirements.
A machine vision based automatic system for real time recognition and sorting of Bangladeshi bank notes.
An efficient machine vision algorithm for real time image analysis and recognition of different features of Bangladeshi bank notes by using an automatic banknotes sorting system is presented.
Characteristics extraction of paper currency using symmetrical masks optimized by GA and neuro-recognition of multi-national paper currency
  • F. Takeda, Toshihiro Nishikage, Y. Matsumoto
  • Computer Science
    1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227)
  • 1998
A unique mask which has a symmetrical masked area against an axis which divides a long side of the currency, equally is proposed, which can obtain the same value from both an upright image and an inverse one of the Currency through the mask processor using the axis-symmetrical mask.
Multiple kinds of paper currency recognition using neural network and application for Euro currency
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  • Computer Science
    Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium
  • 2000
This paper reports an enhanced neuro-recognition system to increase the number of recognition patterns using axis-symmetrical mask and two image sensors, and applies this method to Euro currency, which will be issued in 2002, using dummy notes.