Cart (Loading....) | Create Account
Close category search window
 

A currency recognition system using negatively correlated neural network ensemble

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Debnath, K.K. ; Dept. of EEE, Khulna Univ. of Eng. & Technol., Khulna, Bangladesh ; Ahdikary, J.K. ; Shahjahan, M.

This paper represents a currency recognition system using ensemble neural network (ENN). The individual neural networks (NN) in an ENN are trained via negative correlation learning. The object of using negative correlation learning (NCL) is to expertise the individuals in an ensemble on different parts or portion of input patterns. The available currencies in the market consist of new, old and noisy ones. It is often difficult for machine to recognize these currencies; therefore we propose a system that uses ENN to identify them. We performed our experiment for seven different types of TAKA (Bangladeshi currency) they are 2, 5, 10, 20, 50, 100 and 500 TAKA. The image of different types note is converted in gray scale and compressed in our desired range. Each pixel of the compressed image is given as an input to the network. This system is able to recognize highly noisy or old image of TAKA. Ensemble network is very useful for the classification of different types of currency. It reduces the chances of misclassification than a single network and ensemble network with independent training. In experimental results we have shown this. We also find good result for similar pattern available in market.

Published in:

Computers and Information Technology, 2009. ICCIT '09. 12th International Conference on

Date of Conference:

21-23 Dec. 2009

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.