A study on eyelid localization considering image focus for iris recognition

  • Authors:

  • Young Kyoon Jang;Byung Jun Kang;Kang Ryoung Park

  • Affiliations:

  • Department of Computer Science, Biometrics Engineering Research Center, Sangmyung University, 7 Hongji-Dong, Chongro-Gu, Seoul 110-743, Republic of Korea;Department of Computer Science, Biometrics Engineering Research Center, Sangmyung University, 7 Hongji-Dong, Chongro-Gu, Seoul 110-743, Republic of Korea;Department of Electronics Engineering, Biometrics Engineering Research Center, Dongguk University, 26, Pil-dong 3-ga, Jung-gu, Seoul 100-715, Republic of Korea

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2008

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Abstract

This paper proposes a robust detection algorithm that can be used to detect eyelid region for iris recognition. This research has the following four advantages and contributions compared to the previous works. First, we interpolate the detected eyelashes and specular reflections, which enable us to determine a more accurate searching area of eyelid. Second, we are able to define a limited eyelid searching area by finding the cross position between the eyelids and the outer boundary of the irises. Third, by using eyelid detection mask considering focus value, we can enhance the eyelid detection performance even in the case of defocused iris image. Fourth, by applying the rotation term into the parabolic Hough transform which fits the detected eyelid candidate points, we can detect the accurate eyelid position even in the case of rotated eye. As the experimental results show, the detection accuracy rates were 91.33% and 98.45% when detecting the upper and lower eyelids, respectively.