Iris Feature Extraction and Recognition Based on Wavelet-Based Contourlet Transform

In view of the limitation of poor direction selectivity about 2-D wavelet transform and the problem of redundancy on contourlet transform, an iris texture feature extraction method based on wavelet-based contourlet transform (WBCT)for obtaining high quality features is proposed in the paper. Firstly...

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Bibliographic Details
Published in:Procedia engineering 2012, Vol.29, p.3578-3582
Main Author: Luo, Zhongliang
Format: Article
Language:English
Subjects:
Feature extraction
Iris recognition
Texture
Wavelet-based contourlet transform
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Summary:In view of the limitation of poor direction selectivity about 2-D wavelet transform and the problem of redundancy on contourlet transform, an iris texture feature extraction method based on wavelet-based contourlet transform (WBCT)for obtaining high quality features is proposed in the paper. Firstly, the preprocessed iris image is decomposed by WBCT, then calculating its energy, mean, standard deviation and Hu invariant moments of each subband of different scales and different directions, and taking them as the eigenvalues of iris image, finally, it tests on four iris image databases by using Euclidean distance. Experimental results show that the algorithm is simple and effective, and obtain better recognition performance.
ISSN:1877-7058
1877-7058
DOI:10.1016/j.proeng.2012.01.534