• DocumentCode
    57510
  • Title

    Generalized Binary Pattern for Eye Detection

  • Author

    Inho Choi ; Daijin Kim

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Pohang Univ. of Sci. & Technol., Pohang, South Korea
  • Volume
    20
  • Issue
    4
  • fYear
    2013
  • fDate
    Apr-13
  • Firstpage
    343
  • Lastpage
    346
  • Abstract
    This letter proposes a novel local structure pattern, the generalized binary pattern (GBP), which can represent all possible binary patterns of ordered comparisons within a 3 × 3 neighborhood. Since most existing local structure patterns consider ordered comparisons of all neighboring pixels (8 or 9 pixels) around a given pixel, the number of possible binary patterns is fixed and limited to 256 (or 511). In contrast, our proposed GBP takes the ordered comparisons of some partial neighboring pixels (2 to 9 pixels) around a given pixel, which generates a total of 502 different structure types and thus extends the number of possible binary patterns to 19,162. Among these possible binary patterns, we choose an effective set of binary patterns for a given problem by means of the AdaBoost feature selection method. Experimental results show that our proposed GBP provides higher eye detection accuracy on the BioID and LFW face databases than other existing local structure patterns.
  • Keywords
    eye; iris recognition; learning (artificial intelligence); AdaBoost feature selection method; BioID face database; LFW face database; eye detection; generalized binary pattern; local structure pattern; Accuracy; Face; Feature extraction; Histograms; Indexes; Transforms; AdaBoost feature selection; eye detection; generalized binary pattern; local structure pattern;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2013.2247396
  • Filename
    6461916