• DocumentCode
    2806083
  • Title

    Fingerprint features extraction using curve-scanned DCT coefficients

  • Author

    Tachaphetpiboon, S. ; Amornraksa, T.

  • Author_Institution
    King Mongkut´´s Univ. of Technol. Thonburi, Bangkok
  • fYear
    2007
  • fDate
    18-20 Oct. 2007
  • Firstpage
    33
  • Lastpage
    36
  • Abstract
    This paper proposes a fingerprint features extraction method using curve-scanned DCT coefficients. Generally, the fingerprint features contained in a fingerprint image, such as ridge line patterns and minutiae point, can be extracted from the DCT domain, and used for fingerprint matching. By considering the oscillate pattern contained in the top-left corner of DCT coefficients, we can divide those coefficients in curve-scanned fashion, extract DCT features from the divided DCT coefficients, and use them for matching purpose. To evaluate the proposed method, we use the k-NN classifier to measure the recognition rate, and compare the results obtained from our extraction method to that from the DWT based method [5] and the zigzag-scanned based method [6]. According to the results, the proposed method outperforms the other two, particularly in both recognition rate and processing time.
  • Keywords
    discrete cosine transforms; feature extraction; fingerprint identification; image classification; image matching; curve-scanned DCT; discrete cosine transforms; fingerprint feature extraction; image matching; k-NN classifier; oscillate pattern; recognition rate measurement; Biometrics; Discrete cosine transforms; Discrete wavelet transforms; Feature extraction; Fingerprint recognition; Gray-scale; Image matching; Paper technology; Pixel; Wavelet domain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, 2007. APCC 2007. Asia-Pacific Conference on
  • Conference_Location
    Bangkok
  • Print_ISBN
    978-1-4244-1374-4
  • Electronic_ISBN
    978-1-4244-1374-4
  • Type

    conf

  • DOI
    10.1109/APCC.2007.4433498
  • Filename
    4433498