High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconfigurable Media Processing
ITCC '01 Proceedings of the International Conference on Information Technology: Coding and Computing
Image understanding for iris biometrics: A survey
Computer Vision and Image Understanding
Toward Accurate and Fast Iris Segmentation for Iris Biometrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
A novel iris segmentation using radial-suppression edge detection
Signal Processing
Robust and accurate iris segmentation in very noisy iris images
Image and Vision Computing
A new iris segmentation method for non-ideal iris images
Image and Vision Computing
A highly accurate and computationally efficient approach for unconstrained iris segmentation
Image and Vision Computing
Feature correlation evaluation approach for iris feature quality measure
Signal Processing
Iris segmentation using geodesic active contours
IEEE Transactions on Information Forensics and Security - Special issue on electronic voting
The UBIRIS.v2: A Database of Visible Wavelength Iris Images Captured On-the-Move and At-a-Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Robust Iris Localization Method Using an Active Contour Model and Hough Transform
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Robust iris verification based on local and global variations
EURASIP Journal on Advances in Signal Processing
Unconstrained iris acquisition and recognition using COTS PTZ camera
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
A robust iris segmentation with fuzzy supports
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
New Methods in Iris Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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The iris technology recognizes individuals from their iris texture with great precision. However, it does not perform well for the non-ideal data, where the eye image may contain non-ideal issues such as the off-axis eye image, blurring, non-uniform illumination, hair, glasses, etc. It is because of their iris localization algorithms, which are developed for the ideal data. In this paper, we propose a reliable iris localization algorithm. It includes localizing a coarse iris location in the eye image using the Hough transform and image statistics; localizing the pupillary boundary using a bi-valued adaptive threshold and the two-dimensional (2D) shape properties; localizing the limbic boundary by reusing the Hough accumulator and image statistics; and finally, regularizing these boundaries using a technique based on the Fourier series and radial gradients. The proposed technique is tested on the public iris databases: CASIA V1, CASIA-IrisV3-Lamp, CASIA-IrisV4-Thousand, IITD V1.0, MMU V1.0, and MMU (new) V2.0. Experimental results obtained on these databases show superiority of the proposed technique over some state of the art iris localization techniques.