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An Accurate Eye Detection Method Using Elliptical Separability Filter and Combined Features

机译:利用椭圆分离滤波器和组合特征的精确人眼检测方法

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摘要

This paper presents an accurate eye detection algorithm using elliptical separability filter and combined features of eyes. First, a histogram back-projection method is utilized to extract the rough face region, and then iris candidates are detected by using elliptical separability filter developed based on Fukui et al.'s separability filter. By calculating the similarities of pairs of iris candidates, we determine the pair of iris, which has the largest similarity among others. The similarity of a pair of iris candidates consists of the separability of the pair of iris candidates, the similarity between VQ histograms and normalized correlation coefficient between the region including the pair of iris candidates and eye template. Experimental results show the iris detection rate of the proposed algorithm of 95.2% for 516 images of 86 persons without spectacles in the AR database.
机译:本文提出了一种使用椭圆可分离性滤波器和眼睛组合特征的精确眼睛检测算法。首先,使用直方图反投影法提取粗糙区域,然后使用基于Fukui等人的可分离性滤波器开发的椭圆可分离性滤波器检测虹膜候选。通过计算成对的虹膜候选者之间的相似度,我们可以确定相似度最大的那对虹膜。一对虹膜候选者的相似性包括一对虹膜候选者的可分离性,VQ直方图之间的相似性以及包括一对虹膜候选者和眼睛模板的区域之间的归一化相关系数。实验结果表明,在AR数据库中,该算法对86例无眼镜的516张图像的虹膜检测率为95.2%。

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