基于改进随机Hough变换的瞳孔识别算法研究  

Research on Pupil Recognition Algorithm Based on Improved Randomized Hough Transform

作　　者：李建森 郭文俊 LI Jiansen;GUO Wenjun(School of Information Engineering,Huangshan College,Huangshan Anhui 245041,China)

机构地区：[1]黄山学院信息工程学院,安徽黄山245041

出　　处：《萍乡学院学报》2024年第3期84-87,共4页Journal of Pingxiang University

基　　金：安徽省教育厅自然科学重点项目“基于稀疏数据的弹性关系模型研究——以村落元数据价值增强为例”(2023AH051371);国家级大学生创新创业训练计划项目“基于深度学习的复杂场景下交通标志识别研究”(202310375055)。

摘　　要：随机Hough变换能够有效地识别图像中的圆形,但容易引入大量无效信息,这严重影响了瞳孔识别的效率。课题组提出了一种改进随机Hough变换的瞳孔识别算法,该算法首先在边缘图像上随机采样一点,然后在该点的连通域上寻找候选圆,最后利用一种确定候选圆的真假方法实现瞳孔识别。该改进方法不仅能有效解决随机Hough变换容易引入大量无效信息的问题,还能大大提高瞳孔识别的准确性和速度。Randomized Hough transform can effectively recognize circles in images,but it can easily introduce a large amount of invalid accumulation information,which seriously affects the accuracy and speed of pupil recognition.To address this issue,the research group has proposed an improved method.This method first randomly samples a point on the edge image,then searches for a candidate circle in the connected domain of that point,and finally uses a true or false method to determine the candidate circle for pupil recognition.This improvement method not only effectively solves the problem of randomized Hough transform easily introducing a large amount of invalid accumulated information,but also greatly improves the accuracy and speed of pupil recognition.

关 键 词：随机HOUGH变换 瞳孔识别 圆检测 无效积累 

分 类 号：G632[文化科学—教育学]