控制与信息技术Issue(6)：48-54,7.DOI:10.13889/j.issn.2096-5427.2025.06.006
地铁车辆轨旁检测系统图像序列匹配算法实现
Implementation of an Image Sequence Matching Algorithm for Trackside Detection System of Metro Vehicles
别必龙 1周宇欣 1范浩彪 1田凯阳 1傅辰冰 1张俊1
作者信息
- 1. 宁波市轨道交通集团有限公司智慧运营分公司,浙江宁波 315000
- 折叠
摘要
Abstract
Relying on the trackside detection system of metro vehicles on Ningbo Line 5,this paper proposes a sequence matching algorithm for the accurate alignment of sample images with reference images,to address issues such as image noise and warping caused by train jolting and environmental changes during detection.The algorithm expands the range of image features through multi-frame stitching and introduces the structural similarity index measure(SSIM)to initially locate the train head.Furthermore,it combines the oriented FAST and rotated BRIEF(ORB)feature point detection algorithm,the K-nearest neighbors(KNN)algorithm,and the random sample consensus(RANSAC)algorithm to ensure accurate matching of feature points and elimination of mismatched points.Quantitative analysis of results from multiple on-site experiments shows that the proposed algorithm can effectively eliminate mismatched points.Under varying conditions such as illumination changes,color differences,and noise interference,it maintained an average re-projection error of less than 1.5 pixels and a correct matching rate of over 92％.The significantly improved robustness and stability of detection system meet the requirements of on-site detection.关键词
轨旁检测系统/图像配准/特征点误匹配/SSIM/RANSAC/ORBKey words
trackside detection system/image registration/feature point mismatch/structural similarity index measure(SSIM)/random sample consensus(RANSAC)/oriented FAST and rotated BRIEF(ORB)分类
信息技术与安全科学引用本文复制引用
别必龙,周宇欣,范浩彪,田凯阳,傅辰冰,张俊..地铁车辆轨旁检测系统图像序列匹配算法实现[J].控制与信息技术,2025,(6):48-54,7.
