DocumentCode :
2085559
Title :
Iris recognition based on Empirical Mode Decomposition
Author :
Min, Han ; Yuhua, Peng ; Weifeng, Sun
Author_Institution :
Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan, China
Volume :
1
fYear :
2008
fDate :
17-19 Nov. 2008
Firstpage :
1054
Lastpage :
1058
Abstract :
Empirical mode decomposition (EMD), a multi-resolution decomposition technique, is adaptive and suitable for nonlinear, non-stationary data analysis. We adopt the EMD approach to decompose the iris images into many ingredients with different frequency range, and exploit the mutual information criterion to extract proper parts of them as features for recognition. The proposed method can solve the problem of illumination variation and eyelid-eyelash occlusion. Experimental results show that the performance of the proposed method is encouraging and comparable to the state-of-the-art iris recognition algorithm.
Keywords :
data analysis; feature extraction; image recognition; image resolution; matrix decomposition; empirical mode decomposition; eyelid-eyelash occlusion; illumination variation; iris recognition algorithm; multiresolution decomposition technique; nonstationary data analysis; Data mining; Eyelashes; Eyelids; Feature extraction; Image recognition; Intelligent systems; Iris recognition; Knowledge engineering; Lighting; Mutual information; Biometrics; feature extraction; iris recognition; mutual information;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent System and Knowledge Engineering, 2008. ISKE 2008. 3rd International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-2196-1
Electronic_ISBN :
978-1-4244-2197-8
Type :
conf
DOI :
10.1109/ISKE.2008.4731085
Filename :
4731085
Link To Document :
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