江苏大学学报（自然科学版）2025，Vol.46Issue(4)：373-381,9.DOI:10.3969/j.issn.1671-7775.2025.04.001
基于双目立体视觉的车道线曲率测量方法
Lane curvature measurement method based on binocular stereo vision
摘要
Abstract
To provide more reliable safety recommendations for vehicles navigating curves,the lane curvature measurement method based on binocular stereo vision was investigated.The binocular camera was calibrated by the MATLAB camera calibration toolbox to obtain intrinsic and extrinsic parameters.The original left and right images from the binocular camera were input into the stereo matching network to generate disparity map.The Sobel edge detection and threshold detection were applied to the region of interest(ROI)in the original left camera image,and the results were fused.The perspective transformation was applied to the fused results within the ROI to obtain binary image.The positions and quantities of white pixels within the ROI were statistically analyzed by the histogram.The lane lines were fitted by the least squares method,and the fitting accuracy was enhanced by Kalman filter prediction algorithm.The pixel coordinates of the lane lines were determined based on the inverse affine transformation and the fitting results.The disparity values within the disparity map were obtained according to the pixel coordinates,and the three-dimensional coordinates of the lane lines relative to the main camera of the binocular system were derived by triangulation.The distance conversion scale between the measured real-world coordinates and the image pixel coordinates was calculated and applied to the lane curvature computation.The results show that by the proposed algorithm integrating Kalman filter prediction for lane line detection and binocular stereo vision for lane curvature radius measurement,the average deviation of 5.98％in the calculated curvature radius of curves is achieved,which can ensure the robustness of lane line fitting for enhancing the accuracy and reliability of the binocular stereo vision-based lane curvature measurement method.关键词
车道线曲率/立体视觉/卡尔曼滤波/最小二乘估计/车辆安全Key words
lane curvature/stereo vision/Kalman filter/least squares approximation/vehicle safety分类
信息技术与安全科学引用本文复制引用
黄晨,李悦彬,孙晓强..基于双目立体视觉的车道线曲率测量方法[J].江苏大学学报（自然科学版）,2025,46(4):373-381,9.基金项目
江苏省科技计划港澳台科技合作项目(BZ2022050,YZ2021183) （BZ2022050,YZ2021183）
中国博士后科学基金资助项目(2021M691847) （2021M691847）
国家重点实验室开放基金资助项目(KFY2207,20201206) （KFY2207,20201206）
