A New Localization Method for Iris Recognition Based on Angular Integral Projection Function

Author(s):  
Ghassan J. Mohammed ◽  
Hong BinRong ◽  
Ann A. Al-Kazzaz ◽  
Maan Younis Abdullah
Author(s):  
Yongliang Zhang ◽  
Xiaozhu Chen ◽  
Xiao Chen ◽  
Dixin Zhou ◽  
Erzhe Cao

2013 ◽  
Vol 441 ◽  
pp. 682-686
Author(s):  
Hong Lin Wan ◽  
Bao Sheng Li ◽  
Hong Sheng Li

Boundary localization is one of the key issues for reliable iris recognition system. For non-ideal iris images, eyelashes or eyelids occlusions and low contrast between iris and sclera will lead to inaccurate boundary localization. Specifically, if the intensive transition from iris to sclera is too smooth, outer boundary localization will be very difficult. To stress the problem, in this paper the boundary localization method is proposed in which nonlinear gray transformation is innovated in outer boundary localization process. The experimental results depict that our algorithm have improved the localization accuracy for non-ideal iris compared to the classical algorithms.


2012 ◽  
Vol 10 (11) ◽  
pp. 111501-111506 ◽  
Author(s):  
Farmanullah Jan Farmanullah Jan ◽  
Imran Usman Imran Usman ◽  
Shahrukh Agha Shahrukh Agha

2013 ◽  
Vol 846-847 ◽  
pp. 986-990
Author(s):  
Tian Ping Li ◽  
Xiao Wei Wang

Boundary localization is one of the key issues for reliable iris recognition system. For degraded iris images, some frequently-occurred cases such as dominant texture patterns, eyelashes or eyelids occlusions, low contrast between iris and sclera, and pupil deviation, will lead to inaccurate boundary localization. Specifically, if the intensive transition from iris to sclera is too smooth, outer boundary localization will be very difficult. To stress the problem, in this paper the boundary localization method is proposed in which nonlinear gray-level transformation is innovated in outer boundary localization process. The experimental results depict that our algorithm have improved the localization accuracy for degraded iris compared to the classical algorithms.


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