吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (01): 198-205.

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Iris recognition based on improved empirical mode decomposition method

LI Huan-li1,2, GUO Li-hong1, CHEN Tao1, YANG Li-mei3, WANG Xin-zui4, DONG Yue-fang4   

  1. 1. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China;
    2. Graduate University of the Chinese Academy of Sciences, Beijing 100039, China;
    3. School of Mechatronic Engineering, Changchun University of Technology, Changchun 130012, China;
    4. Suzhou Institute of Biomedical Engineering and Technology, Suzhou 215163, China
  • Received:2011-11-16 Online:2013-01-01 Published:2013-01-01

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Abstract: An iris recognition method based on improved empirical mode decomposition is proposed. First, the normalized iris image is decomposed based by row and then column to generate the different layer intrinsic mode components of the image. Second, the feature image is obtained by binarizing the components useful for the iris recognition. Third, the Hamming distance matching vector is obtained by horizontal and vertical shift match. Finally, the improved standard deviation of the matching vector is calculated, which is used as the threshold for iris recognition. This method is tested using CASIA1, CASIA2, CASIA3-Interval and MMU1 databases. Experiment results show that this method can extract the binary feature effectively, with faster speed and higher correct recognition rate.

Key words: computer application, empirical mode decomposition, improved standard deviation, iris recognition

CLC Number: 

  • TP391.4
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