• DocumentCode
    2150936
  • Title

    Eyelid and eyelash detection method based on morphology

  • Author

    Yan, Youbo ; Xie, Mei

  • Author_Institution
    Coll. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • Volume
    1
  • fYear
    2010
  • fDate
    26-28 Feb. 2010
  • Firstpage
    678
  • Lastpage
    681
  • Abstract
    The reliable detection of the occlusion iris image in the polar domain is required to improve the performance of iris recognition. Estimated the occluding and refine a much more accurate iris mask before iris feature extraction is essential step in the iris recognition. In this paper, we propose a method for detecting occlusion and refining mask accurately based on morphology. Compared with traditional method which detected sequence is eyelid-eyelash and distinguish eyelash based on threshold alone. Out method segment image by using the connectivity of the eyelash which is the base of the region grow. It guards against the noise in the process of the thresholding and decreases the computer load significantly. This method is applied to the CASAI version 3 databases and shows good performance.
  • Keywords
    computer graphics; feature extraction; image segmentation; iris recognition; mathematical morphology; eyelash detection method; eyelid detection method; iris feature extraction; iris segmentation; morphology; occlusion iris image detection; Educational institutions; Eyelashes; Eyelids; Image databases; Image segmentation; Iris recognition; Morphology; Reflection; Reliability engineering; Shape; component; connectivity; injection; iris mask estimation; iris recognition; iris segmentation; morphology; region grow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-5585-0
  • Electronic_ISBN
    978-1-4244-5586-7
  • Type

    conf

  • DOI
    10.1109/ICCAE.2010.5451295
  • Filename
    5451295