This work describes a new hybrid method for accurate iris segmentation from full-face images independently of the ethnicity of the subject. It is based on a combination of three methods: facial key-point detection, integro-differential operator (IDO) and mathematical morphology. First, facial landmarks are extracted by means of the Chehra algorithm in order to obtain the eye location. Then, the IDO is applied to the extracted sub-image containing only the eye in order to locate the iris. Once the iris is located, a series of mathematical morphological operations is performed in order to accurately segment it. Results are obtained and compared among four different ethnicities (Asian, Black, Latino and White) as well as with two other iris segmentation algorithms. In addition, robustness against rotation, blurring and noise is also assessed. Our method obtains state-of-the-art performance and shows itself robust with small amounts of blur, noise and/or rotation. Furthermore, it is fast, accurate, and its code is publicly available.

中文翻译：

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一种在远距离可见光图像上准确分割虹膜的混合方法

这项工作描述了一种新的混合方法，可以从全脸图像中准确地分割虹膜，而与对象的种族无关。它基于三种方法的组合：面部关键点检测，整数微分算子（IDO）和数学形态学。首先，借助Chehra算法提取面部标志，以获取眼睛位置。然后，将IDO应用于仅包含眼睛的提取子图像，以定位虹膜。虹膜定位后，将执行一系列数学形态学运算，以准确分割虹膜。获得并比较了四个不同种族（亚洲，黑人，拉丁裔和白人）以及其他两个虹膜分割算法的结果。此外，还评估了抗旋转，模糊和抗噪的鲁棒性。我们的方法获得了最先进的性能，并且在少量模糊，噪声和/或旋转的情况下表现出强大的性能。此外，它是快速，准确的，并且其代码是公开可用的。