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A Novel Paper Currency Recognition using Fourier Mellin Transform, Hidden Markov Model and Support Vector Machine

by Abbas Yaseri, Seyed Mahmoud Anisheh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 61 - Number 7
Year of Publication: 2013
Authors: Abbas Yaseri, Seyed Mahmoud Anisheh
10.5120/9939-3997

Abbas Yaseri, Seyed Mahmoud Anisheh . A Novel Paper Currency Recognition using Fourier Mellin Transform, Hidden Markov Model and Support Vector Machine. International Journal of Computer Applications. 61, 7 ( January 2013), 17-22. DOI=10.5120/9939-3997

@article{ 10.5120/9939-3997,
author = { Abbas Yaseri, Seyed Mahmoud Anisheh },
title = { A Novel Paper Currency Recognition using Fourier Mellin Transform, Hidden Markov Model and Support Vector Machine },
journal = { International Journal of Computer Applications },
issue_date = { January 2013 },
volume = { 61 },
number = { 7 },
month = { January },
year = { 2013 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume61/number7/9939-3997/ },
doi = { 10.5120/9939-3997 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:08:27.557760+05:30
%A Abbas Yaseri
%A Seyed Mahmoud Anisheh
%T A Novel Paper Currency Recognition using Fourier Mellin Transform, Hidden Markov Model and Support Vector Machine
%J International Journal of Computer Applications
%@ 0975-8887
%V 61
%N 7
%P 17-22
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A paper currency recognition system has a wide range of applications such as self receiver machines for automated teller machines and automatic good-selling machines. In this paper a new paper currency recognition system based on Fourier-Mellin transform, Markovian characteristics and Support Vector Machine (SVM) is presented. In the first, a pre-processing algorithm by Fourier-Mellin transform is performed. The key feature of Fourier-Mellin transform is that it is invariant in rotation, translation and scale of the input image. Then, obtained image is segmented and markovian characteristics of each segment have been utilized to construct a feature vectors. These vectors are then fed into SVM classifier for paper currency recognition. In order to evaluate the effectiveness of the system several experiments are carried out. Experimental result indicates that the proposed method achieved high accuracy rate in paper currency recognition.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Paper currency recognition Fourier-Mellin Transform Markovian characteristics Support Vector Machine

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