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Impact of out-of-focus blur on iris recognition

机译：离焦模糊对虹膜识别的影响

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Iris recognition has expanded from controlled settings to uncontrolled settings (on the move, from a distance) where blur is more likely to be present in the images. More research is needed to quantify the impact of blur on iris recognition. In this paper we study the effect of out-of-focus blur on iris recognition performance from images captured with out-of-focus blur produced at acquisition. A key aspect to this study is that we are able to create a range of blur based on changing focus of the camera during acquisition. We quantify the produced out-of-focus blur based on the Laplacian of Gaussian operator and compare it to the gold standard of the modulation transfer function (MTF) of a calibrated black/white chart. The sharpness measure uses an unsegmented iris images from a video sequence with changing focus and offers a good approximation of the standard MTF. We examined the effect of the 9 blur levels on iris recognition performance. Our results have shown that for moderately blurry images (sharpness at least 50%) the drop in performance does not exceed 5% from the baseline (100% sharpness).
机译：虹膜识别已从受控设置扩展到非受控设置（在移动中，从远处），在这些设置中，图像中更容易出现模糊。需要更多的研究来量化模糊对虹膜识别的影响。在本文中，我们将从在采集时产生的散焦模糊所捕获的图像中研究散焦模糊对虹膜识别性能的影响。这项研究的一个关键方面是，我们能够根据采集过程中相机焦点的变化来创建一定范围的模糊。我们基于高斯算子的拉普拉斯算子对产生的离焦模糊进行量化，并将其与校准的黑白图表的调制传递函数（MTF）的金标准进行比较。清晰度测量使用焦点变化的视频序列中未分割的虹膜图像，并提供与标准MTF的良好近似。我们检查了9个模糊级别对虹膜识别性能的影响。我们的结果表明，对于中等模糊的图像（清晰度至少为50％），性能下降不会超过基线（清晰度为100％）的5％。

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