The input of the iris classification network based on deep learning has two forms: one is the coarsely located iris region of interest; the other is the normalized iris. To solve the problem of whether it is necessary to normalize the iris, experiments are carried out on the above two input forms, and the results show that the iris normalization is still the best choice. To adapt to the visual characteristics of the neural network, an iris normalization processing method is proposed: starting from 90 deg, the iris circle is mapped to polar coordinates and the normalized rectangle is cropped, rotated, and spliced. Experimental and visualization results show that the proposed iris normalization strategy has better results of iris recognition than other normalization methods.

中文翻译：

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基于深度学习的虹膜识别归一化虹膜是最佳选择吗？

基于深度学习的虹膜分类网络的输入有两种形式：一种是粗定位的虹膜感兴趣区域；另一个是标准化的虹膜。针对虹膜是否需要归一化的问题，对以上两种输入形式进行了实验，结果表明虹膜归一化仍然是最佳选择。为适应神经网络的视觉特性，提出虹膜归一化处理方法：从90度开始，将虹膜圆映射到极坐标，对归一化的矩形进行裁剪、旋转、拼接。实验和可视化结果表明，所提出的虹膜归一化策略比其他归一化方法具有更好的虹膜识别结果。