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Iris Location Algorithm Based on Union-Find-Set and Block Search

机译:基于Union-Find-Set和块搜索的虹膜位置算法

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In view of the problem of unstable recognition effect and low robustness of a traditional iris location algorithm, an iris location algorithm based on union-find-set and block search is proposed. Firstly, the inner circle of the iris is roughly positioned by the method of retrieval, and then, the Hough transform is used to accurately locate the pupil. After that, the convolution operation is used to roughly locate the outer circle, and then, the original image is partitioned to search. And the grayscale change in the gray histogram of the screenshot is observed to accurately locate the outer circle. The obtained iris and the iris obtained by the traditional localization algorithm are processed by the same iris recognition algorithm. The results show that the proposed image is more effective in image recognition and has good robustness.
机译:鉴于传统虹膜位置算法的不稳定识别效果和低稳健性的问题,提出了一种基于Union-Find-Set和块搜索的虹膜位置算法。 首先,虹膜的内圈大致通过检索方法定位,然后,使用霍夫变换来准确地定位瞳孔。 之后,卷积操作用于大致定位外圈,然后,原始图像被划分以搜索。 观察屏幕截图的灰度直方图的灰度变化,以准确地定位外圈。 所获得的虹膜和通过传统定位算法获得的虹膜通过相同的虹膜识别算法处理。 结果表明,所提出的图像在图像识别方面更有效,具有良好的鲁棒性。

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