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Computer vision based currency classification system

by Bhupendra Singh, Pankaj Badoni, Kuldeep Verma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 16 - Number 4
Year of Publication: 2011
Authors: Bhupendra Singh, Pankaj Badoni, Kuldeep Verma
10.5120/1999-2695

Bhupendra Singh, Pankaj Badoni, Kuldeep Verma . Computer vision based currency classification system. International Journal of Computer Applications. 16, 4 ( February 2011), 34-38. DOI=10.5120/1999-2695

@article{ 10.5120/1999-2695,
author = { Bhupendra Singh, Pankaj Badoni, Kuldeep Verma },
title = { Computer vision based currency classification system },
journal = { International Journal of Computer Applications },
issue_date = { February 2011 },
volume = { 16 },
number = { 4 },
month = { February },
year = { 2011 },
issn = { 0975-8887 },
pages = { 34-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume16/number4/1999-2695/ },
doi = { 10.5120/1999-2695 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:04:00.173972+05:30
%A Bhupendra Singh
%A Pankaj Badoni
%A Kuldeep Verma
%T Computer vision based currency classification system
%J International Journal of Computer Applications
%@ 0975-8887
%V 16
%N 4
%P 34-38
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

There are numerous problems associated with current system which are solving the problem of automatic currency classification. Some of the problems administered are like scaling, rotation and noise in the form of missing valuable data in printing or due to the wear and tear of currency notes. In our system we are first aligning the image horizontally along the x axis and after that foreground of the image is removed by detecting the location of edges, and once we have got the processed image we can apply any of the techniques for classification. Over here we are using fast template matching for recognizing the value of the currency. Once we get result after template matching we can classify the currency into different categories like 10, 50,100,500 and 1000. In our system we are aiming at the improvement on existing system by adding useful and robust pre-processing techniques which has been missing in most of the recent works done so far.

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Index Terms

Computer Science
Information Sciences

Keywords

Rotation invariant background removal correlation template matching

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