Abstract

Iris-based identification is a well-known and widely used technology. However, its use in mobile devices is limited due to the algorithmic complexity of the existing methods and their low universality with respect to various capturing conditions. A method for finding the iris area by approximating its boundaries by two circles is proposed. The relative error of determining the circle parameters must not exceed 5%. Convolutional neural networks optimized with respect to the number of parameters are applied. The proposed method outperforms the classical (not based on neural networks) methods for solving this segmentation problem. The operation of the proposed method is checked on open iris image databases.

中文翻译：

---

使用卷积神经网络查找虹膜

摘要

基于虹膜的识别是一项众所周知且广泛使用的技术。然而，由于现有方法的算法复杂性以及它们在各种捕获条件方面的普遍性较低，其在移动设备中的使用受到限制。提出了一种通过将虹膜区域的边界近似为两个圆来找到虹膜区域的方法。确定圆弧参数的相对误差不得超过5％。应用了针对参数数量优化的卷积神经网络。所提出的方法优于解决该分割问题的经典方法（不是基于神经网络）。在开放的虹膜图像数据库上检查了所提出方法的操作。