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基于图像特征的双目测距系统的研究 被引量:6

Research on Binocular Ranging System Based on Image Features
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摘要 针对双目视觉测距中测量误差大、图像信息单一、实时性差等问题,提出一种基于ORB(oriented fast and rotated brief)特征的双目测距方法。对视频帧进行中值滤波处理,提取图像ORB特征,通过实验选出匹配效果最好的汉明距离。对筛选后的匹配点进行RANSAC(random sample consensus)模型估计,去除误匹配,分析视差和真实距离的模型关系,构建最优的测距模型并在实验平台上进行验证。结果表明:所提方法比其他双目测距方法具有测距精确、运行速度快、鲁棒性强的优势,能够实时显示图中特征的距离信息。 Aiming at the problems of large measurement error,single image information,and poor real-time performance in binocular vision ranging,a binocular ranging method based on ORB(oriented fast and rotated brief)features is proposed.Median filtering is performed on the video frame,the ORB feature of the image is extracted,and the Hamming distance with the best matching effect is selected through experiments.The RANSAC(random sample consensus)model estimation is performed on the selected matching points,the mismatches are removed,the model relationship between parallax and true distance is analyzed,the optimal ranging model is constructed and verified on the experimental platform.The results show that the proposed method has the advantages of accurate ranging,fast running speed and strong robustness compared with other binocular ranging methods,and can display the distance information of the features in the image in real time.
作者 杨敬辉 刘德康 杜万和 邢立宁 Yang Jinghui;Liu Dekang;Du Wanhe;Xing Lining(Engineering Department of Shanghai Polytechnic University,Shanghai 201209,China;School of Systems Engineering,NationalUniversity of Defense Technology,Changsha 410073,China)
出处 《系统仿真学报》 CAS CSCD 北大核心 2022年第3期624-632,共9页 Journal of System Simulation
基金 上海市一流研究生项目(A30DB201011)。
关键词 ORB(oriented fast and rotated brief) 特征匹配 RANSAC(random sample consensus) 模型优化 双目测距 oriented fast and rotated brief(ORB) feature matching random sample consensus(RANSAC) model optimization binocular ranging
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