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 and Ocular Biometrics - The Salient Features
IMVIP '08 Proceedings of the 2008 International Machine Vision and Image Processing Conference
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Comparing and Improving Algorithms for Iris Recognition
IMVIP '09 Proceedings of the 2009 13th International Machine Vision and Image Processing Conference
Iris recognition based on non-local comparisons
SINOBIOMETRICS'04 Proceedings of the 5th Chinese 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
IEEE Transactions on Circuits and Systems for Video Technology
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Iris pattern is considered to be the most discriminatory of facial biometrics. However, changes in iris texture appearance occur with age, disease and medication. This study of high resolution images of 238 irides, captured with a specialised biomicroscope at three and six month intervals, and classified according to texture, measured recognition failure rates resulting from the application of local and non-local feature extraction techniques. In both local and non-local comparisons, minimum failure rates of 20.3% and 13.8% were noted, respectively. The complex fibre pattern formation of the iris results in variability in identification with differing failure rates depending on texture.