Real-time texture synthesis by patch-based sampling
ACM Transactions on Graphics (TOG)
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Personal Identification Based on Iris Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Iris Segmentation Method for Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
UBIRIS: a noisy iris image database
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
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Iris recognition is a method used to identify people based on the analysis of the eye iris. A typical iris recognition system is composed of four phases: (1) image acquisition and preprocessing, (2) iris localization and extraction, (3) iris features characterization, and (4) comparison and matching. A novel contribution in the step of characterization of iris features is introduced by using a Hammersley's sampling algorithm and accumulated histograms. Histograms are computed with data coming from sampled sub-images of iris. The optimal number and dimensions of samples is obtained by the simulated annealing algorithm. For the last step, couples of accumulated histograms iris samples are compared and a decision of acceptance is taken based on an experimental threshold. We tested our ideas with UBIRIS database; for clean eye iris databases we got excellent results.