Ordinal Measures for Iris Recognition
Ordinal Measures for Iris Recognition
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DOI：
10.1109/tpami.2008.240
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发表时间：
2009-12
影响因子：
23.6
通讯作者：
Zhenan Sun;T. Tan
中科院分区：
文献类型：
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作者：
Zhenan Sun;T. Tan
虹膜图像包含丰富的纹理信息，可用于身份认证。虹膜识别中的一个关键问题是如何使用一组紧凑的特征（虹膜特征）来最好地表示这种纹理信息。在本文中，我们建议使用顺序措施虹膜特征表示的虹膜区域之间的定性关系，而不是精确测量虹膜图像结构的特征。这样的表示可能会丢失一些图像特定的信息，但它实现了良好的独特性和鲁棒性之间的权衡。我们表明，顺序措施是虹膜图案的内在特征，在很大程度上不受光照变化。此外，有序测度的紧凑性和低计算复杂度使得能够实现高效的虹膜识别。有序测度是图像分析中有用的一般概念，并且可以导出许多变体用于有序特征提取。在本文中，我们开发了多瓣差分滤波器来计算顺序措施，灵活的瓣内和瓣间参数，如位置，规模，方向和距离。在三个公开的虹膜图像数据库上的实验结果验证了所提出的有序特征模型的有效性。
Images of a human iris contain rich texture information useful for identity authentication. A key and still open issue in iris recognition is how best to represent such textural information using a compact set of features (iris features). In this paper, we propose using ordinal measures for iris feature representation with the objective of characterizing qualitative relationships between iris regions rather than precise measurements of iris image structures. Such a representation may lose some image-specific information, but it achieves a good trade-off between distinctiveness and robustness. We show that ordinal measures are intrinsic features of iris patterns and largely invariant to illumination changes. Moreover, compactness and low computational complexity of ordinal measures enable highly efficient iris recognition. Ordinal measures are a general concept useful for image analysis and many variants can be derived for ordinal feature extraction. In this paper, we develop multilobe differential filters to compute ordinal measures with flexible intralobe and interlobe parameters such as location, scale, orientation, and distance. Experimental results on three public iris image databases demonstrate the effectiveness of the proposed ordinal feature models.