一种新的红外眼图像瞳孔检测算法

Huabiao Qin, Xinliang Wang, Mingju Liang, Weihong Yan
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引用次数: 12

摘要

为了提高眼球注视跟踪技术的精度,提出了一种基于边缘梯度方向信息的Hough变换瞳孔检测算法。根据红外角膜反射背景下瞳孔像素的特征,利用二维霍夫变换,结合边缘梯度方向和固定范围的离散瞳孔半径,对参数空间离散变换点进行计数,定位瞳孔中心。它能有效地滤除噪声,减少离散变换点统计量,计算瞳孔参数。实验结果表明,该算法比以往的模型具有更高的精度和实时性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel pupil detection algorithm for infrared eye image
In order to improve the accuracy of the eye gaze tracking technology, this paper presents a novel pupil detection algorithm based on Hough Transform with edge gradient direction information. According to the pupil pixel features in the context of infrared corneal reflection, taking advantage of two-dimensional Hough Transform, combining the edge gradient direction and a fixed range of discrete pupil radius, this algorithm counts parameter space discrete transform points to locate pupil center. It effectively filters out noise, reduces the discrete transform point statistics and calculates pupil's parameters. Experimental results show that the algorithm has a higher accuracy and real-time than the previous models.
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