Journal of Northeastern University Natural Science ›› 2017, Vol. 38 ›› Issue (2): 180-184.DOI: 10.12068/j.issn.1005-3026.2017.02.006

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Iris Localization Method Based on SIFT and SDM

WANG Qi, ZHANG Tie, ZHANG Xiao-meng, ZHANG Xiang-de   

  1. School of Sciences, Northeastern University, Shenyang 110819, China.
  • Received:2016-02-05 Revised:2016-02-05 Online:2017-02-15 Published:2017-03-03
  • Contact: ZHANG Xiang-de
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Abstract: To improve the speed and stability of iris localization, an SDM(supervised descend method)-based iris localization algorithm was proposed. Firstly, radial symmetry transformation was adopted to localize pupil roughly, then, an integro-differential operator was used to segment pupil accurately. Secondly, SIFT(scale invariant feature transform)features were selected to describe the characteristic information of the outer boundary of the iris and eyelids. Thirdly, the SDM algorithm was employed to determine the key points on the outer boundary and eyelids.Finally,the least square algorithm was used to determine the parameters of the outer boundary, the upper and lower eyelids. Experimental results show that the proposed algorithm can greatly improve the efficiency and stability of iris localization.

Key words: iris recognition, iris localization, SIFT, SDM, least square algorithm

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