DocumentCode :
232340
Title :
Gaze angle estimate and correction in iris recognition
Author :
Tao Yang ; Stahl, Joachim ; Schuckers, Stephanie ; Fang Hua ; Boehnen, Chris B. ; Karakaya, Mahmut
Author_Institution :
Dept. of Comput. Sci., Clarkson Univ., Potsdam, NY, USA
fYear :
2014
fDate :
9-12 Dec. 2014
Firstpage :
132
Lastpage :
138
Abstract :
Conventional iris recognition using a full frontal iris image has reached a very high accuracy rate. In this paper, we focus on processing off-angle iris images. Previous research has shown that it is possible to correct off-angle iris images, but knowledge of the angle was needed. Very little work has focused on iris angle estimation which can be used for angle correction. In this paper, we describe a two-phase angle estimation based on the geometric features of the ellipse. Angle correction is accomplished by projective transformation. Evaluation of this angle estimation and correction method includes a 3D eyeball simulator, and performance test on the West Virginia University Off-Angle Dataset.
Keywords :
iris recognition; 3D eyeball simulator; West Virginia University Off-Angle dataset; full frontal iris image; gaze angle correction; gaze angle estimation; geometric features; iris angle estimation; iris recognition; off-angle iris image correction; off-angle iris image processing; performance test; projective transformation; two-phase angle estimation; Biological system modeling; Educational institutions; Estimation; Image edge detection; Iris recognition; Shape; Three-dimensional displays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Biometrics and Identity Management (CIBIM), 2014 IEEE Symposium on
Conference_Location :
Orlando, FL
Type :
conf
DOI :
10.1109/CIBIM.2014.7015454
Filename :
7015454
Link To Document :
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