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A New Pupil Detection Algorithm Based on Circular Hough Transform Approaches

机译:一种基于圆形Hough变换方法的新型瞳孔检测算法

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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:本文介绍了一种基于圆形霍夫变换方法的新瞳孔检测算法。所提出的算法包括自适应定量二值化过程,通过使用带拉普拉斯操作员执行某些形态操作和图像轮廓检测的瞳孔重建阶段。为了保存计算资源,将圆形霍夫变换应用于二值化眼图像的边缘,并为在非均匀和可变照明条件下捕获的嘈杂眼图像提供更好的结果。基于CHT的算法在三个不同和高度代表性数据库的五个像素上实现了5个像素的检出速率,累计了1324个眼睛图像。

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