河北工业科技2024，Vol.41Issue(6)：418-425,8.DOI:10.7535/hbgykj.2024yx06003
基于改进SURF的图像特征点匹配算法
Image feature point matching algorithm based on improved SURF
摘要
Abstract
In order to improve the accuracy of feature point matching in 3D reconstruction of images,an image feature point matching algorithm based on improved SURF was proposed.Firstly,the 64-dimension descriptor of SURF was upgraded to 128 dimensions.Secondly,the KD-Tree module was introduced into the SURF algorithm,and the BBF(best bin first)nearest neighbor query mechanism was used to implement feature point matching.Finally,after rotating and scaling changes on the same data set,feature point matching experiments were performed on the images by using the traditional algorithm and the improved SURF algorithm,respectively,and then the effectiveness of the improved SURF(speeded-up robust features)algorithm was verified.The results show that the improved SURF algorithm achieves a feature matching accuracy of 89.19%,which is improved 17.62 percentage points,and the number of feature false matches decreases from 85 to 31,significantly reducing the matching error of feature points.The running time is shortened from 1.956 seconds to 1.647 seconds,further improving the running speed of the algorithm.The improved SURF algorithm has the characteristics of high accuracy,less errors and fast speed,which can provide reference for 3D reconstruction feature matching.关键词
图像处理/特征点匹配/SURF算法/KD-Tree/三维重建Key words
image processing/feature point matching/SURF algorithm/KD-Tree/3D reconstruction分类
信息技术与安全科学引用本文复制引用
王震洲,张森,宁超,王建超..基于改进SURF的图像特征点匹配算法[J].河北工业科技,2024,41(6):418-425,8.基金项目
河北省教育厅青年基金(QN2023185) （QN2023185）
河北省高等学校科学技术重点研究项目(ZD2020318) （ZD2020318）
