首页|基于自适应几何约束ORB的红外双目测距方法

基于自适应几何约束ORB的红外双目测距方法

扫码查看
原文链接
  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
针对传统特征匹配算法计算效率低、误匹配率高和双目视觉测量精度不足等问题,提出了一种基于自适应几何约束和随机抽样一致性方法的ORB(Oriented FAST and Rotated BRIEF)红外双目测距方法.首先,通过 FAST(Features from Accelerated Segment Test)算法与 BRIEF(Binary Robust Independent Elementary Features)算法检测并描述关键点,采用快速最近邻搜索的算法完成特征点初始匹配.然后,根据初始匹配点对的斜率与距离选择相应的阈值,构建基于斜率与距离的几何约束,剔除明显错误匹配点对.最后利用随机抽样一致性方法去除异常点完成精匹配,结合热像仪标定参数计算出目标物体的距离.实验结果表明,改进的 ORB 算法与传统算法相比,具有较好的特征点质量和较高的测量精度,测距平均绝对误差为 1.64%,具有较好的实用价值.
Infrared Binocular Ranging Method Based on Adaptive Geometrically Constrained ORB
An ORB infrared binocular ranging method based on adaptive geometric constraints and the random sampling consistency method is proposed to address the issues of low computational efficiency,high mismatching rates,and insufficient accuracy in binocular vision measurements by traditional feature matching algorithms.First,key points are detected and described using the FAST and BRIEF algorithms,and the initial matching of feature points is performed using the fast library for approximate nearest neighbors(FLANN)algorithm.Then,based on the slope and distance of the initial matching pairs,appropriate thresholds are selected,and geometric constraints based on these parameters are constructed to eliminate incorrect matching pairs.Finally,a random sample consensus(RANSAC)method is used to remove anomalous points and complete the fine matching.The distance of the target object is calculated by combining the thermal camera calibration parameters.Experimental results show that the improved ORB algorithm yields higher quality feature points and greater measurement accuracy compared to traditional algorithms,with an average absolute error of distance measurements at 1.64%,demonstrating its practical value.

oriented fast and rotated brief(ORB)thermal infraredbinocular distance measurementadaptive thresholdgeometric constraints

李淮周、王帅军、王宏、曹祥红、白振鹏、李森

展开 >

郑州轻工业大学 建筑环境工程学院,河南 郑州 450001

ORB算法 热红外 双目测距 自适应阈值 几何约束

河南省科技攻关项目河南省科技攻关项目河南省科技攻关项目河南省高等学校重点科研项目郑州轻工业大学博士科研基金

22210222007121210221053523210232102122A4700142018BSJJ053

2024

红外技术
昆明物理研究所 中国兵工学会夜视技术专业委员会

红外技术

CSTPCD北大核心
影响因子：0.914
ISSN：1001-8891
年,卷(期)：2024.46(7)