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A New Pupil Detection Algorithm Based on Circular Hough Transform Approaches

机译:基于循环霍夫变换方法的学生检测新算法

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In this paper a new pupil detection algorithm based on circular Hough transform approaches is presented. The proposed algorithm includes an adaptive quantitative binarization procedure, a pupil reconstruction stage by using certain morphological operations and the image contour detection performed with the Laplace operator. To save the computing resources, the circular Hough transform is applied on the edge of the binarized eye image and provides better results for noisy eye image captured in nonuniform and variable lighting conditions. The CHT based algorithm achieves a detection rate at five pixels higher than 82% for three different and highly representative databases, totalizing 1324 eye images.
机译:本文提出了一种新的基于圆形霍夫变换方法的瞳孔检测算法。所提出的算法包括自适应定量二值化过程,通过使用某些形态学运算的瞳孔重建阶段以及使用Laplace算子执行的图像轮廓检测。为了节省计算资源,将圆形霍夫变换应用于二值化眼图图像的边缘,并为在不均匀和可变照明条件下捕获的嘈杂眼图提供了更好的结果。基于CHT的算法对三个不同且具有高度代表性的数据库在五个像素处的检测率高于82%,总共1324个眼图。

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