DocumentCode :
3536584
Title :
Feature Extraction of Currency Notes: An Approach Based on Wavelet Transform
Author :
Rajaei, Amir ; Dallalzadeh, Elham ; Imran, Mohammad
Author_Institution :
Dept. of Studies in Comput. Sci., Univ. of Mysore, Mysore, India
fYear :
2012
fDate :
7-8 Jan. 2012
Firstpage :
255
Lastpage :
258
Abstract :
In this paper, we propose to extract the texture features of currency note images. To extract the features, first the Discrete Wavelet Transform (DWT) in particular Daubechies 1 (DB1) is utilized on a currency note and the approximate coefficient matrix of the transformed image is obtained. A set of coefficient statistical moments are then extracted from the approximate efficient matrix. The extracted features are stored in a feature vector. The extracted features can be used for recognition, classification and retrieval of currency notes.
Keywords :
approximation theory; discrete wavelet transforms; feature extraction; financial data processing; image classification; image retrieval; image texture; matrix algebra; object recognition; statistical analysis; Daubechies 1; approximate coefficient matrix; approximate efficient matrix; coefficient statistical moments; currency note image classification; currency note image recognition; currency note image retrieval; discrete wavelet transform; feature vector; texture feature extraction; Approximation methods; Discrete wavelet transforms; Feature extraction; Image color analysis; Pattern recognition; Wavelet analysis; Currency notes; Discrete Wavelet Transform; Feature Extraction; Statistical Moments;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computing & Communication Technologies (ACCT), 2012 Second International Conference on
Conference_Location :
Rohtak, Haryana
Print_ISBN :
978-1-4673-0471-9
Type :
conf
DOI :
10.1109/ACCT.2012.53
Filename :
6168372
Link To Document :
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