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'Hallucinating Irises' - Dealing with Partial #x00026; Occluded Iris Regions

机译:“幻觉虹膜” - 处理部分和闭塞鸢尾区

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In this paper, we examine a novel image-filling algorithm to fill the occluded and partial regions of the iris. In iris recognition, these occlusions naturally appear due to eye-lids being partially closed, eye movements and eye-lashes. Additionally, specular reflections arising from the iris-camera illuminator are present and produce occlusion artifacts on the iris region. In the polar representation of iris images, additional `nuisance' parameters include image regions containing the pupil and sclera due to inaccurate iris segmentations. Thus, for accurate iris recognition, it is important to reduce the effect of these nuisance parameters so that the performance of the iris recognition system can be maximized. Typically, a mask region (automatic or manual) is defined to ignore occluded or affected iris regions from such nuisance artifacts. However, in the feature extraction stage, especially using Gabor type extraction, the features near the edge of these artifacts are also affected due to the tail supports of these filters that overflow on occluded irises. We propose a novel method for filling in the occluded regions by synthesizing the iris pattern from this current exemplar image and show that a significant improvement on the Iris Challenge Evaluation (ICE) dataset can be made.
机译:在本文中,我们检查了一种新颖的图像填充算法,以填补虹膜的遮挡和部分区域。在虹膜识别中,这些闭塞由于眼睑被部分封闭,眼睛运动和眼睛睫毛而自然出现。另外,从虹膜相机照明器产生的镜面反射存在并在虹膜区域产生遮挡伪像。在虹膜图像的极性表示中,额外的“滋扰”参数包括由于不准确的虹膜分割而包含瞳孔和巩膜的图像区域。因此,为了精确的虹膜识别,重要的是减少这些滋扰参数的效果,从而可以最大化虹膜识别系统的性能。通常,定义掩模区域(自动或手动)以忽略来自这种滋扰伪像的遮挡或影响虹膜区域。然而,在特征提取阶段,特别是使用Gabor类型提取,由于这些滤波器的尾部支撑,这些伪影的边缘附近的特征也受到覆盖的虹膜溢出的尾部支撑。我们提出了一种通过从该电流示例图像中合成虹膜模式来填充遮挡区域的新方法,并表明可以制造对虹膜挑战评估(ICE)数据集的显着改善。

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