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首页> 外文期刊>Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on >Iris Recognition Using Possibilistic Fuzzy Matching on Local Features
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Iris Recognition Using Possibilistic Fuzzy Matching on Local Features

机译：利用可能的局部特征模糊匹配进行虹膜识别

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摘要

In this paper, we propose a novel possibilistic fuzzy matching strategy with invariant properties, which can provide a robust and effective matching scheme for two sets of iris feature points. In addition, the nonlinear normalization model is adopted to provide more accurate position before matching. Moreover, an effective iris segmentation method is proposed to refine the detected inner and outer boundaries to smooth curves. For feature extraction, the Gabor filters are adopted to detect the local feature points from the segmented iris image in the Cartesian coordinate system and to generate a rotation-invariant descriptor for each detected point. After that, the proposed matching algorithm is used to compute a similarity score for two sets of feature points from a pair of iris images. The experimental results show that the performance of our system is better than those of the systems based on the local features and is comparable to those of the typical systems.
机译：在本文中，我们提出了一种具有不变性质的新颖的可能性模糊匹配策略，该策略可以为两组虹膜特征点提供鲁棒而有效的匹配方案。另外，采用非线性归一化模型在匹配之前提供更准确的位置。此外，提出了一种有效的虹膜分割方法，以细化检测到的内部和外部边界以平滑曲线。对于特征提取，采用Gabor滤波器从笛卡尔坐标系中的分割虹膜图像中检测局部特征点，并为每个检测到的点生成旋转不变描述符。之后，所提出的匹配算法用于从一对虹膜图像中为两组特征点计算相似度得分。实验结果表明，我们的系统性能优于基于局部特征的系统，并且与典型系统相当。

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