基于高斯滤波的虹膜凹陷检测

Bo Shen, Yong Xu, Guangming Lu, David Zhang
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引用次数: 9

摘要

腔隙是虹膜的典型征象,腔隙的检测在虹膜自动诊断中具有重要意义。本文首先介绍了虹膜图像中的腔隙检测。虽然目前文献中有各种各样的边缘检测算法,但它们在提取图像中的各种特征时并不总能得到可接受的结果。空白区通常具有较差的局部对比度,现有边缘检测算法的应用效果不理想。因此,我们提出了一种基于高斯滤波器的凹痕检测方法,该方法对噪声具有鲁棒性。将垂直方向的高斯滤波用于归一化虹膜图像,大大降低了该方法的时间复杂度。实验结果表明了该方法的有效性。
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Detecting Iris Lacunae Based on Gaussian Filter
Lacunae is a typical sign of iris, and the detection of lacunae is of great importance in automatic iris diagnosis. In this paper, we first introduce the lacunae detection in iris images. Although current literature has a variety of edge detection algorithms, they do not always lead to acceptable results in extracting various features in an image. Lacunae usually have poor local contrast and the application of existing edge detection algorithms yield results which are not satisfactory. Thus, we proposed a lacunae detecting approach based on Gaussian filters, which is robust to noise. When the Gaussian filter in the vertical orientation is implemented to normalized iris image, the time complexity of this approach is reduced considerably. Experimental results show the validity of this approach.
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