计量学报2025，Vol.46Issue(3)：323-328,6.DOI:10.3969/j.issn.1000-1158.2025.03.03
一种基于SURF-ORB的改进图像配准算法
An Improved Image Registration Algorithm Based on SURF-ORB
摘要
Abstract
An improved image registration algorithm based on SURF-ORB is proposed.Establish speeded up robust features(SURF)image pyramid,detect oriented FAST and rotated BRIEF(ORB)feature points on it and use 256 bit binary characters as feature vectors to describe feature points.The nearest neighbor method matches feature points.Filter matching points by utilizing the similar properties of neighborhood average gray difference,Euclidean distance,matching point line and x-axis angle among the correct matching points.The k-means clustering(k-means)algorithm is improved,using points with a density greater than the threshold as the center point of the class,clustering,deleting classes with a sum of squared errors greater than the threshold and reclassifying the remaining feature points into the reserved classes.The random sample consensus(RANSAC)algorithm is improved,merging all transformation matrixes'interior points into a set and classifying the matching points in the set that meet the error distance threshold with the candidate optimal transformation model into its inner points.Use the least squares method to recalculate the transformation matrix with all its interior points to obtain a more accurate solution.The experimental results show that the number of feature points extracted by this algorithm is about 32%less than that of SURF and ORB algorithm,the matching accuracy is improved by about 16%,and the operation time is increased by about 0.26%.关键词
机械视觉/图像配准/尺度空间/SURF算法/ORB算法/特征点分组/变换模型Key words
machine vision/image registration/scale space/SURF algorithm/ORB algorithm/feature points grouping/transform model分类
通用工业技术引用本文复制引用
尚明姝,王克朝,高玉宝..一种基于SURF-ORB的改进图像配准算法[J].计量学报,2025,46(3):323-328,6.基金项目
黑龙江省重点研发项目(GY2023JD0051) （GY2023JD0051）
黑龙江省自然科学基金(LH2024F011) （LH2024F011）
黑龙江省哲学社会科学基金(21KGB083 （）
22KGB142) （）
