• DocumentCode
    2597170
  • Title

    A feature and appearance based method for eye detection on gray intensity face images

  • Author

    Kith, Visal ; El-Sharkawy, Mohamed ; Bergeson-Dana, Tonya ; El-Ramly, Salwa ; Elnoubi, Said

  • Author_Institution
    Sch. of Eng. & Technol., Purdue Univ., Indianapolis, IN
  • fYear
    2008
  • fDate
    25-27 Nov. 2008
  • Firstpage
    41
  • Lastpage
    47
  • Abstract
    This paper presents a robust and precise eye detection algorithm on gray intensity face images. Our method combines the strength of two existing methods which are a feature based method and an appearance based method to detect and locate a precise pupil center. It includes the following three steps. First, the feature based method is used. The method uses a projection function to detect all possible regions of each left and right eye. Second, the appearance based method is used to filter out all non eye regions, and keep only one region for each left and right eye. All possible regions will go through a principal component analysis (PCA). Third, a modified hybrid projection function is used to locate the pupil center for both eyes. The experimental results show that the proposed method has an efficient performance with the accuracy of more than 90.52%.
  • Keywords
    eye; face recognition; feature extraction; filtering theory; image classification; learning (artificial intelligence); principal component analysis; eye detection algorithm; eye training image; feature-based method; filtering method; gray intensity face image; images classification; principal component analysis; projection function; pupil center; Eyes; Face detection; Face recognition; Filters; Humans; Infrared imaging; Iris recognition; Lighting; Principal component analysis; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Engineering & Systems, 2008. ICCES 2008. International Conference on
  • Conference_Location
    Cairo
  • Print_ISBN
    978-1-4244-2115-2
  • Electronic_ISBN
    978-1-4244-2116-9
  • Type

    conf

  • DOI
    10.1109/ICCES.2008.4772963
  • Filename
    4772963