The fast iris image clarity evaluation based on Tenengrad and ROI selection
The fast iris image clarity evaluation based on Tenengrad and ROI selection
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DOI：
10.1117/12.2302509
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发表时间：
2018-04
期刊：
影响因子：
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通讯作者：
Shuqin Gao;Min Han;Xu Cheng
中科院分区：
文献类型：
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作者：
Shuqin Gao;Min Han;Xu Cheng
在虹膜识别系统中，虹膜图像的清晰度是影响识别效果的一个重要因素。在识别过程中，模糊的图像可能会被虹膜自动识别系统拒绝，从而导致识别失败。因此，在进行虹膜图像识别之前，有必要对虹膜图像的清晰度进行评估。考虑到现有的虹膜图像清晰度评价方法，本文提出了一种快速评价虹膜图像清晰度的算法。该算法首先利用瞳孔内光点的特征确定参考点，提取感兴趣区域（ROI），然后利用Tenengrad算子对虹膜图像的清晰度进行评价。实验结果表明，本文提出的虹膜图像定义算法能够准确区分不同清晰度的虹膜图像，且算法具有计算复杂度低、效率高的优点。
In iris recognition system, the clarity of iris image is an important factor that influences recognition effect. In the process of recognition, the blurred image may possibly be rejected by the automatic iris recognition system, which will lead to the failure of identification. Therefore it is necessary to evaluate the iris image definition before recognition. Considered the existing evaluation methods on iris image definition, we proposed a fast algorithm to evaluate the definition of iris image in this paper. In our algorithm, firstly ROI (Region of Interest) is extracted based on the reference point which is determined by using the feature of the light spots within the pupil, then Tenengrad operator is used to evaluate the iris image’s definition. Experiment results show that, the iris image definition algorithm proposed in this paper could accurately distinguish the iris images of different clarity, and the algorithm has the merit of low computational complexity and more effectiveness.