Image Representation Using 2D Gabor Wavelets
IEEE Transactions on Pattern Analysis and Machine Intelligence
The lifting scheme: a construction of second generation wavelets
SIAM Journal on Mathematical Analysis
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
Location of the Pupil-Iris Border in Slit-Lamp Images of the Cornea
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Personal Identification Based on Iris Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iris Extraction Based on Intensity Gradient and Texture Difference
WACV '08 Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision
Iris feature extraction and matching based on multiscale and directional image representation
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
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
IEEE Transactions on Circuits and Systems for Video Technology
A reliable iris recognition algorithm based on reverse biorthogonal wavelet transform
Pattern Recognition Letters
Computer Vision and Image Understanding
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Iris recognition has been demonstrated to be an efficient technology for personal identification. In this work, methods to perform iris encoding using bi-orthogonal wavelets and directional bi-orthogonal filters are proposed and compared. All the iris images are enhanced using the wavelet domain in-band de-noising method. This method is shown to improve the iris segmentation results. A framework to assess the iris image quality based on occlusion, contrast, focus and angular deformation is introduced and used as part of a novel adaptive matching technique based on the assessed iris image quality. Adaptive matching presents improved performance when compared against the Hamming distance method. Four different databases are used to analyze the system performance. The first two databases include popular CASIA and high resolution University of Bath databases. Results obtained for these databases compare with results from the literature, in terms of speed as well as accuracy. The other two databases have challenging off-angle (WVU database) and uncontrolled (Clarkson database) iris images and are used to assess the limits of system performance. Best results are achieved for directional bi-orthogonal filter based encoding technique combined with the adaptive matching method with EER values of 0.07%, 0.15%, 0.81% and 1.29% for the four databases, which reflect highly competent performance and high correlation with the quality of the iris images.