In general, iris recognition systems with linear normalization model ignore the Pupil Light Reflex - PLR. The PLR is responsible for adjusting light intensity reaches the retina and causes nonlinear iris contraction and dilation movements that generates significant differences between enrolled images and test images. This paper has proposed a method to reduce the influence of iris dynamics examined by decidability (d) and Equal Error Rate (EER), obtained in the comparison between iris codes in different states of dilation. The method has used the Dynamic Time Warping (DTW) technique to compare the Histogram of Gradients Oriented (HoG) vectors extracted from the iris texture. In this way, the most discriminated characteristics between test images and the gallery had been aligned and compared, considering a nonlinear deformation of the iris tissue caused by the PLR. The experimental results, using dynamic images, indicate the system performance worsen when compared to images in different states of contraction. For a direct comparison between iris well contracted with well-dilated iris, the proposed method improves the decidability from 3.50 to 4.39 and the EER from 9.69% to 3.36%.

中文翻译：

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虹膜生物特征识别过程中的动态时间扭曲


一般来说，具有线性归一化模型的虹膜识别系统忽略瞳孔光反射（PLR）。 PLR 负责调节到达视网膜的光强度，并引起非线性虹膜收缩和扩张运动，从而在登记图像和测试图像之间产生显着差异。本文提出了一种减少虹膜动态影响的方法，通过可判定性（d）和等错误率（EER）进行检查，这些方法是在不同扩张状态下的虹膜代码之间的比较中获得的。该方法使用动态时间规整（DTW）技术来比较从虹膜纹理中提取的梯度定向直方图（HoG）向量。通过这种方式，考虑到 PLR 引起的虹膜组织的非线性变形，测试图像和图库之间最有区别的特征被对齐和比较。使用动态图像的实验结果表明，与不同收缩状态的图像相比，系统性能更差。为了对收缩良好的虹膜与扩张良好的虹膜进行直接比较，所提出的方法将可判定性从 3.50 提高到 4.39，将 EER 从 9.69% 提高到 3.36%。