CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

A Survey on various Techniques of Coin Detection and Recognition

by Deepika Mehta, Anil Sagar
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 69 - Number 5
Year of Publication: 2013
Authors: Deepika Mehta, Anil Sagar
10.5120/11840-7568

Deepika Mehta, Anil Sagar . A Survey on various Techniques of Coin Detection and Recognition. International Journal of Computer Applications. 69, 5 ( May 2013), 29-32. DOI=10.5120/11840-7568

@article{ 10.5120/11840-7568,
author = { Deepika Mehta, Anil Sagar },
title = { A Survey on various Techniques of Coin Detection and Recognition },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 69 },
number = { 5 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 29-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume69/number5/11840-7568/ },
doi = { 10.5120/11840-7568 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:29:27.035483+05:30
%A Deepika Mehta
%A Anil Sagar
%T A Survey on various Techniques of Coin Detection and Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 69
%N 5
%P 29-32
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Coin which act as the basic need of the human being and today life of human beings depends solely on machines so the detection and recognition of coin is very important rather than counting coins manually. One can easily detect and recognize the coins by using various techniques. This paper focuses on the variety of techniques that have being used to detect and recognize the coins of different denomination. A variety of techniques and approaches have being proposed such as Circular Hough Transform, Artificial neural networks, heuristics etc which further help in recognition of coin. The performance rate of detection and recognition was upto 97. 74% as computed by Neural Networks . The performance analyzed was on the basis of variety of parameters used such as size, weight, thickness and many more. Future improvement can be done detection and recognition of overlapping of coins.

References
  1. Jain, N. , and Jain, N. 2012 Coin Recognition Using Circular Hough Transform, International Journal of Electronics Communication and Computer Technology, Vol 2, Issue 3, 2249-7838.
  2. Modi, S. and Bawa, S., "Automated Coin Recognition System using ANN", International Journal of Computer Applications Vol. 26(4), pp.13-18, July 2011. Published by Foundation of Computer Science, New York, USA.
  3. Liangwongsan S. , Marungsri B. , Oonsivilai R. and Oonsivilai A. 2011 Extracted Circle Hough Transform and Circle Defect Detection Algorithm, World Academy of Science, Engineering and Technology.
  4. Pendse M. and Wang Y. Automated Coin Detection on Android Phone.
  5. Velu C. M. and Vivekanandan P. 2009 Indian Coin Recognition System of Image Segmentation by Heuristic Approach and Hough Transform, International Journal Open Problems Compt. . Math. , Vol 2, Issue 2.
  6. Reisert M. , Ronneberger O. and Burkhardt H. An Efficient Based Registration Technique for Coin Recognition. Albert-Ludwig University, Georges Koehler Allee 52.
  7. McNeill S. , Schipper J. , Sellers T. and Nechyba M. C. Coin Recognition using Vector Quantization and Histogram Modelling. Machine Intelligence Laboratory, University of Florida at Gainesville, FL 32611.
  8. Reisert M. , Ronneberger O. and Burkhardt H. A Fast and Reliable Coin Recognition System. University of Freiburg, Computer Science Department, 79110 Freiburg i. Br. , Germany.
  9. Tresanchez M. , Palleja T. , Teixido M. and Palacin J. 2009 Using the Optical Mouse Sensor as a Two-Euro Counterfeit Coin Detector, Sensors, 7083-7096.
  10. Nolle M. , Penz H. , Rubik M. , Mayer K. , Hollander I. , and Grance R. 2003 Dagobert – A New Coin Recognition and Sorting System, proceeding in VIIth Digital Image Computing:Techniques and Applications, Sydney.
Index Terms

Computer Science
Information Sciences

Keywords

Hough Transform Coin Detection Coin Recognition

Powered by PhDFocusTM