Design of Gabor Filter Banks for Iris Recognition

Author(s):  
Chia-te Chou ◽  
Sheng-wen Shih ◽  
Duan-yu Chen
2014 ◽  
Vol 602-605 ◽  
pp. 1610-1613
Author(s):  
Ming Hai Yao ◽  
Na Wang ◽  
Jin Song Li

With the increasing number of internet user, the authentication technology is more and more important. Iris recognition as an important method for identification, which has been attention by researchers. In order to improve the predictive accuracy of iris recognition algorithm, the iris recognition method is proposed based feature discrimination and category correlation. The feature discrimination and category correlation are calculated by laplacian score and mutual information. The formula about feature discrimination and category correlation are built. Aiming at texture characteristic of iris image, the multi-scale circular Gabor filter is used to feature extraction. The computational efficiency of algorithm is improved. In order to verify the validity of the algorithm, the CASIA iris database of Chinese Academy of Sciences is used to do the experiment. The experimental results show that our method has high predictive accuracy.


2017 ◽  
Vol 1 (4-2) ◽  
pp. 175
Author(s):  
Abdulrahman Aminu Ghali ◽  
Sapiee Jamel ◽  
Kamaruddin Malik Mohamad ◽  
Nasir Abubakar Yakub ◽  
Mustafa Mat Deris

With the prominent needs for security and reliable mode of identification in biometric system. Iris recognition has become reliable method for personal identification nowadays. The system has been used for years in many commercial and government applications that allow access control in places such as office, laboratory, armoury, automated teller machines (ATMs), and border control in airport. The aim of the paper is to review iris recognition algorithms. Iris recognition system consists of four main stages which are segmentation, normalization, feature extraction and matching. Based on the findings, the Hough transform, rubber sheet model, wavelet, Gabor filter, and hamming distance are the most common used algorithms in iris recognition stages.  This shows that, the algorithms have the potential and capability to enhanced iris recognition system. 


Author(s):  
Qixian Zhang ◽  
Xiaodong Zhu ◽  
Yuanning Liu ◽  
Guang Huo ◽  
Guangyu Wang ◽  
...  

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