Paper Info
Title
An Iris localization method for noisy infrared iris images
Abstract
Iris segmentation is an important step in iris biometrics and becomes more challenging when iris images are noisy. Iris segmentation process localizes iris in the iris image and detects eyelids also. The proposed method localizes iris in noisy frontal view iris images captured under near infrared (NIR) illumination and having noise issues such as lighting and specular reflections, eyeglasses, low contrast, non-uniform illuminations and occlusions by heavy eyebrows, eyelids, eyelashes and hair. The proposed method is based on circular Hough transform (CHT) and an integro-differential operator (IDO) derived by taking motivation from Daugman's IDO. The pupil is localized using image binarization followed by CHT based algorithm and iris's outer boundary is detected by searching a limited image domain for maximum gray difference between iris and sclera using the proposed IDO. The method was tested on noisy images from two public NIR iris databases: MMU V2.0 and CASIA-Iris-Thousand V4.0. The average accuracy of the proposed method is 99.05 % and average time cost per image is 415 ms. Comparison of results of the proposed method with some published state-of-art iris localization methods proves its novelty.
Year
DOI
Venue
2015
10.1109/ICSIPA.2015.7412191
2015 IEEE International Conference on Signal and Image Processing Applications (ICSIPA)
Keywords
Field
DocType
Iris segmentation,Iris localization,Circular Hough transform,Integro-differential operator,Iris biometrics,Iris recognition
Iris recognition,Computer vision,Noise measurement,Pattern recognition,Computer science,Segmentation,Pupil,Hough transform,Image segmentation,Sclera,Artificial intelligence,Biometrics
Conference
Citations 
PageRank 
References 
0
0.34
13
Authors
3
Name
Order
Citations
PageRank
Vineet Kumar119626.07
Abhijit R. Asati2135.70
Anu Gupta383.99