A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Representation Using 2D Gabor Wavelets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Personal Identification Based on Iris Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iris Recognition Using Wavelet Features
Journal of VLSI Signal Processing Systems
Iris Recognition Using Collarette Boundary Localization
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
UBIRIS: a noisy iris image database
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
An iterative algorithm for fast iris detection
IWBRS'05 Proceedings of the 2005 international conference on Advances in Biometric Person Authentication
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal Processing
New Methods in Iris Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Efficient iris recognition by characterizing key local variations
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
A novel and efficient feedback method for pupil and iris localization
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part II
Biometric verification of subjects using saccade eye movements
International Journal of Biometrics
Speed-up multi-stage non-cooperative iris recognition
International Journal of Biometrics
A comprehensive approach for sclera image quality measure
International Journal of Biometrics
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In this paper, we propose an efficient and accurate technique to process iris biometric. Our approach handles degraded quality of eye images, occlusion of eyelids and eyelashes. Our approach considers non-circular pupil and iris boundary. With our approach it is possible to store an iris template with 304 bits only unlike 1024 bits used in majority of the existing approaches. Further, we assign different weights to different iris regions enabling us to compare two iris templates with a lesser number of features and thus achieving better accuracy. Experimental results on several iris databases establish the efficacy of our approach.