Iris Recognition Based on Local Feature Point Matching
Ruihui Zhu, Jinfeng Yang, Renbiao Wu · 2006
Recently, iris recognition has been paid more attention due to its high reliability in personal identification. But iris feature extraction is easily affected by some practical factors, such as inaccurate localization, occlusion, nonlinear elastic deformation and so on. In order to solve the problem, this paper presents an efficient algorithm of iris feature extraction based on scale invariant feature transform (SIFT). Experimental results show that the proposed algorithm can reduce iris preprocessing, describe iris local properties effectively and have encouraging iris recognition performance