• DocumentCode
    3245337
  • Title

    Feature extraction using extended central projection

  • Author

    Lan, Rushi ; Yang, Jianwei ; Jiang, Yong ; Feng, Xiaoxia

  • Author_Institution
    Sch. of Math & Stat., Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
  • fYear
    2012
  • fDate
    15-17 July 2012
  • Firstpage
    327
  • Lastpage
    331
  • Abstract
    A novel feature extraction method is proposed in this paper. Dislike contour-based or region-based approaches, an object is first converted to a closed curve by extended central projection (ECP). The derived curve not only keeps the affine transform information, but also is very robust to noise. Then whitening transform is performed to the curve such that the affine transformation is simplified to a rotation only. Finally, Fourier transform are employed to remove the rotation. Several experiments have been conducted to evaluate the performance of the proposed method. Experimental results show that the proposed method has a powerful discrimination ability, and is more robust to noise.
  • Keywords
    Fourier transforms; affine transforms; feature extraction; object recognition; ECP; Fourier transform; affine transform information; contour-based approach; extended central projection; feature extraction method; object recognition; region-based approach; whitening transform; Accuracy; Covariance matrix; Feature extraction; Noise; Pattern recognition; Shape; Transforms; Affine transformation; Extended central projection (ECP); Feature extraction; Object recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Analysis and Pattern Recognition (ICWAPR), 2012 International Conference on
  • Conference_Location
    Xian
  • ISSN
    2158-5695
  • Print_ISBN
    978-1-4673-1534-0
  • Type

    conf

  • DOI
    10.1109/ICWAPR.2012.6294802
  • Filename
    6294802