Statistical Richness of Visual Phase Information: Update on Recognizing Persons by Iris Patterns
International Journal of Computer Vision
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iris Recognition with Low Template Size
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Personal Identification Based on Iris Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Half-Eye Wavelet Based Method for Iris Recognition
ISDA '05 Proceedings of the 5th International Conference on Intelligent Systems Design and Applications
Biometrics: Personal Identification in Networked Society
Biometrics: Personal Identification in Networked Society
Iris-based personal authentication using a normalized directional energy feature
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Iris verification using correlation filters
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Iris feature extraction using independent component analysis
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal Processing
Efficient iris recognition by characterizing key local variations
IEEE Transactions on Image Processing
Optimal features subset selection and classification for iris recognition
Journal on Image and Video Processing - Regular
Noisy Iris Verification: A Modified Version of Local Intensity Variation Method
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Application of evolutionary algorithms for iris localization
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Algorithm for iris code organization and searching for iris recognition system
Proceedings of the International Conference and Workshop on Emerging Trends in Technology
A region-based Iris feature extraction method based on 2D-wavelet transform
BioID_MultiComm'09 Proceedings of the 2009 joint COST 2101 and 2102 international conference on Biometric ID management and multimodal communication
Robust iris verification based on local and global variations
EURASIP Journal on Advances in Signal Processing
An efficient iris coding based on gauss-laguerre wavelets
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Selection of parameters in iris recognition system
Multimedia Tools and Applications
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Accurate iris detection is a crucial part of an iris recognition system. One of the main issues in iris segmentation is coping with occlusion that happens due to eyelids and eyelashes. In the literature, some various methods have been suggested to solve the occlusion problem. In this paper, two different segmentations of iris are presented. In the first algorithm, a circle is located around the pupil with an appropriate diameter. The iris area encircled by the circular boundary is used for recognition purposes then. In the second method, again a circle is located around the pupil with a larger diameter. This time, however, only the lower part of the encircled iris area is utilized for individual recognition. Wavelet-based texture features are used in the process. Hamming and harmonic mean distance classifiers are exploited as a mixed classifier in suggested algorithm. It is observed that relying on a smaller but more reliable part of the iris, though reducing the net amount of information, improves the overall performance. Experimental results on CASIA database show that our method has a promising performance with an accuracy of 99.31%. The sensitivity of the proposed method is analyzed versus contrast, illumination, and noise as well, where lower sensitivity to all factors is observed when the lower half of the iris is used for recognition.