Extraction of complex wavelet features for iris recognition

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Extraction of complex wavelet features for iris recognition
This paper presents a new feature extraction method for iris recognition. Since two dimensional complex wavelet transform (2D-CWT) does not only keep wavelet transform’s properties of multiresolution decomposition analysis and perfect reconstruction, but also adds its new merits: approximate shift invariance, good directional selectivity for 2-D image, and limited redundancy, which are useful for iris feature extraction. So, a set of high frequency 2D-CWT coefficients are selected as features for iris recognition. The phase information of the coefficients is used for feature encoding and Hamming distance is adopted for classification. Experimental results show that the proposed algorithm can get good recognition rate.
XiaoFu He, Pengfei Shi
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICPR
Authors XiaoFu He, Pengfei Shi
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