SIFT based iris recognition with normalization and enhancement

نویسندگان

  • Gongping Yang
  • Shaohua Pang
  • Yilong Yin
  • Yanan Li
  • Xuzhou Li
چکیده

SIFT is a novel and promising method for iris recognition. However, some shortages exist in many related methods, such as difficulty of feature extraction, feature loss, and noise point introduction. In this paper, a new method named SIFT-based iris recognition with normalization and enhancement is proposed for achieving better performance. In Comparison with other SIFT-based iris recognition algorithms, the proposed method can overcome the difficulties of extreme point extraction and exclude the noise points without feature loss. Experimental results demonstrate that the normalization and enhancement steps are crucial for SIFT-based iris recognition, and the proposed method can achieve satisfactory recognition performance.

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عنوان ژورنال:
  • Int. J. Machine Learning & Cybernetics

دوره 4  شماره 

صفحات  -

تاریخ انتشار 2013