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Based on this idea, we propose a new user dependent method for iris recognition.
Hosseini et al. [8] proposed a feature extraction method for iris images taken under VL using a shape analysis method.
As we mentioned briefly in Section 1, Daugman, in [5], proposed a method for iris segmentation using Snake model [21].
In our work, we used their idea about the bit consistency in iris code and developed an applied method for iris recognition systems.
A novel intelligent reference method for iris segmentation-level fusion is presented, which uses a learning-based approach predicting ground truth segmentation performance from quality indicators and model-based fusion to create combined boundaries.
The suggested framework and reference method for iris segmentation fusion is presented in detail in Section 3. Section 4 introduces the databases and algorithms under test and gives a detailed presentation and analysis of experiments.
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Other methods exist for iris localization, including [12, 16].
Details for building method of IRIS and urban and rural areas are available on http://www.insee.fr/fr/methodes).fr/fr/methodes
In this paper, we therefore propose a method for cross-spectral iris images matching.
In [7], an easy to difficult method has been used for iris localization by, first, determining high-contrast parts of boundary, and then, detecting outer boundary and eyelids.
However, this method is only suitable for iris matching and cannot be directly combined with existing systems.
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