An eye detection method robust to eyeglasses for mobile iris recognition

Yujin Jung, Dongik Kim, Byungjun Son, Jaihie Kim

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


Finding the accurate position of an eye is crucial for mobile iris recognition system in order to extract the iris region quickly and correctly. Unfortunately, this is very difficult to accomplish when a person is wearing eyeglasses because of the interference from the eyeglasses. This paper proposes an eye detection method that is robust to eyeglass interference in mobile environment. The proposed method comprises two stages: eye candidate generation and eye validation. In the eye candidate generation stage, multi-scale window masks consisting of 2 × 3 subblocks are used to generate all image blocks possibly containing an eye image. In the ensuing eye validation stage, two methods are employed to determine which blocks actually contain true eye images and locate their precise positions as well: the first method searches for the glint of an NIR illuminator on the pupil region. If this first method fails, the next method computes the intensity difference between the assumed pupil and its surrounding region using multi-scale 3 × 3 window masks. Experimental results show that the proposed method detects the eye position more accurately and quickly than competing methods in the presence of interference from eyeglass frames.

Original languageEnglish
Pages (from-to)178-188
Number of pages11
JournalExpert Systems with Applications
Publication statusPublished - 2017 Jan 1

Bibliographical note

Publisher Copyright:
© 2016 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • General Engineering
  • Computer Science Applications
  • Artificial Intelligence


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