DocumentCode :
3750120
Title :
Noise reduction for iris recognition using adaptive fuzzy filtering
Author :
Arezou Banitalebi Dehkordi;Syed A.R. Abu-Bakar
Author_Institution :
Computer Vision, Video, Image Processing Research Lab, Dept. of Electronics and Computer Eng., Faculty of Electrical Eng., Universiti Teknologi Malaysia, Malaysia
fYear :
2015
Firstpage :
399
Lastpage :
403
Abstract :
Reduction of influences of noise is an important stage in the iris recognition systems. In order to reduce effects of noise such as, eyelashes, eyelids and light illumination, this paper proposes noise reduction method based on an adaptive fuzzy filtering. The proposed method has low complexity and adaptive window size of filling filter. The Fuzzification is based on density of noise pixels within the filter´s window and intensity values of noise and iris patterns. The Adaptive window size of filter enables the filling filter to perform noise reduction for different densities of noise pixels in the iris region. The results of applying proposed adaptive fuzzy filtering method on the CASIA V3.0 iris database, with genuine acceptance rate equals 99.72% show the success of the proposed method.
Keywords :
"Iris recognition","Eyelashes","Gabor filters","Filling","Adaptive filters","Noise reduction"
Publisher :
ieee
Conference_Titel :
Signal and Image Processing Applications (ICSIPA), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/ICSIPA.2015.7412223
Filename :
7412223
Link To Document :
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