• 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