基于改进四叉树的ORB特征均匀分布算法

ORB feature uniform distribution algorithm based on improved quadtree

针对ORB特征在图像上分布不均匀的问题,提出一种基于改进四叉树的特征均匀分布算法。通过计算图像灰度均值与方差选取FAST角点的初始提取阈值,采用改进的四叉树对特征点进行筛选,对不同金字塔层设置不同的四叉树深度以提高计算效率,减少特征冗余,采用均匀度函数对特征的均匀度进行量化。实验结果表明,改进算法提高了ORB特征的均匀度,特征提取时间相比传统算法减少10%以上,有效提高了特征提取的均匀度和效率。

Aiming at the problem of uneven distribution of ORB feature point,an ORB feature extraction algorithm based on improved quadtree was presented.The gray mean and variance of the image were calculated,and the initial extraction threshold of FAST corner points was determined accordingly.The improved quadtree was used to manage feature points,and different quadtree depths were set for different pyramid layers to improve the calculation efficiency and reduce feature redundancy.The uniformity function was used to quantify the uniformity of the feature.Experimental results demonstrate that the modified algorithm can improve the uniformity of ORB features and reduce feature extraction time by more than 10%compared to traditional algorithm,the efficiency and uniformity of feature extraction was effectively improved.