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
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal 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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We present a new approach for iris recognition based on a sampling scheme. Iris recognition is a method to identify persons, based on the analysis of the eye iris. A typical iris recognition system is composed of four phases: image acquisition and preprocessing, iris localization and extraction, iris features characterization, and comparison and matching. The main contribution in this work is in the step of characterization of iris features by using sampling methods and accumulated histograms. These histograms are built from data coming from sampled subimages of iris. In the comparison and matching step, a comparison is made between accumulated histograms of couples of iris samples, and a decision of accept/reject is taken based on samples differences and on a threshold calculated experimentally. We tested two sampling methods: random and Hammersley, and conduct experiments with UBIRIS database. Under certain conditions we found a rate of successful identifications in the order of 100 %.