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Reseach Article

A Review Paper on Currency Recognition System

by Ami Shah, Komal Vora, Jay Mehta
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 20
Year of Publication: 2015
Authors: Ami Shah, Komal Vora, Jay Mehta
10.5120/20264-2669

Ami Shah, Komal Vora, Jay Mehta . A Review Paper on Currency Recognition System. International Journal of Computer Applications. 115, 20 ( April 2015), 1-4. DOI=10.5120/20264-2669

@article{ 10.5120/20264-2669,
author = { Ami Shah, Komal Vora, Jay Mehta },
title = { A Review Paper on Currency Recognition System },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 20 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number20/20264-2669/ },
doi = { 10.5120/20264-2669 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:55:21.495850+05:30
%A Ami Shah
%A Komal Vora
%A Jay Mehta
%T A Review Paper on Currency Recognition System
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 20
%P 1-4
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, an algorithm based on the frequency domain feature extraction method is discussed for the detection of currency. This method efficiently utilizes the local spatial features in a currency image to recognize it. The entire system is pre-processed for the optimal and efficient implementation of two dimensional discrete wavelet transform (2D DWT) which is used to develop a currency recognition system. A set of coefficient statistical moments are then extracted from the approximate efficient matrix. The extracted features can be used for recognition, classification and retrieval of currency notes. The classification result will facilitate the recognition of fake currency mainly using serial number extraction by implementing OCR. It is found that the proposed method gives superior results.

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Index Terms

Computer Science
Information Sciences

Keywords

Feature extraction classification discrete wavelet transform textural feature currency recognition OCR fake currency security thread serial number RBI marks.