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An Enhanced Iris Segmentation Algorithm Using Circle Hough Transform

机译:基于圆霍夫变换的改进虹膜分割算法

摘要

Iris segmentation is the most contesting issue in the iris recognition system, since the result of this stage will mar or break the iris recognition system effectiveness. Therefore, a very careful attention has to be paid in the segmentation process if only an accurate result is expected; this depends on the accuracy of the detected pupil center. In this paper we proposed a new method to localize the center of the pupil which is concentric with the iris image by employing 8-neighbourhood operators. This parameter is then fed to a Circle Hough Transform to enhanced iris segmentation processing speed and accuracy. The occlusions due to eyelids and eyelashes noise are detected by applying canny edge operator. The experiment is conducted using 320 iris images from CASIA standard dataset, and the result shows that the proposed method had a high accuracy rate.
机译:虹膜分割是虹膜识别系统中最有争议的问题,因为此阶段的结果将损害或破坏虹膜识别系统的有效性。因此,如果仅期望得到准确的结果,则在分割过程中必须非常小心;这取决于检测到的瞳孔中心的准确性。在本文中,我们提出了一种新方法,该方法通过使用8邻域算子来定位与虹膜图像同心的瞳孔中心。然后将此参数输入到Circle Hough变换中,以提高虹膜分割的处理速度和准确性。通过应用Canny边缘算子可以检测到由于眼睑和睫毛噪声引起的咬合。使用来自CASIA标准数据集的320个虹膜图像进行了实验,结果表明该方法具有较高的准确率。

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