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作 者:赵丽丽 张丽 唐阳山[1] ZHAO Li-li;ZHANG Li;TANG Yang-shan(School of Automobile and Traffic Engineering,Liaoning University of Technology,Jinzhou 121001,China;Jinzhou Public Transport Co.,Ltd,Jinzhou 121001,China)
机构地区:[1]辽宁工业大学汽车与交通工程学院,辽宁锦州121001 [2]锦州市公共交通有限责任公司,辽宁锦州121001
出 处:《辽宁工业大学学报(自然科学版)》2022年第6期357-361,366,共6页Journal of Liaoning University of Technology(Natural Science Edition)
摘 要:针对目前人工标定特征点存在误差大等不足之处,提出了一种自动识别特征点的方法。首先设定合适的检测区进行摄影测量时的相机标定,其次利用图像预处理、图像分割及形态学滤波处理(图像膨胀、开运算)等去除噪点,从而识别出车辆轮胎,利用函数bwtraceboundary来获取轮胎边界,然后依据圆的各种公式来获取相应的参数,求出轮胎的半径。同时再对其圆心进行标记,从而标注出轮胎中心点,进而精确识别轮胎中心特征点及其坐标。并通过坐标转换关系确定特征点的实际坐标,最后运用交通事故视频车速鉴定标准进行车速估计,从而实现提高测速精度的目的。实验验证表明,利用该方法对车速进行估计,其估计结果误差降低了3.07%。In view of the shortcomings of the current manual calibration feature point such as large errors, a method for automatic identification of feature points is proposed. Firstly, the appropriate detection area is set for camera calibration during photogrammetry, and secondly, image preprocessing,image segmentation, and morphological filtering processing(image expansion, opening operation) are used to remove noise to identify vehicle tires, and the function bwtraceboundary is used to obtain the tire boundary, and then obtain the corresponding parameters according to the various formulas of the circle, and find the radius of the tire. At the same time, its center is marked to mark the tire center point,and then accurately identify the tire center feature point and its coordinates. The actual coordinates of the feature points are determined through the coordinate conversion relationship, and finally the speed estimation is carried out by using the traffic accident video speed identification standard, so as to achieve the purpose of improving the speed measurement accuracy. Experimental results show that the error of the estimation result is reduced by 3.07% by using this method to estimate the vehicle speed.
分 类 号:U491.3[交通运输工程—交通运输规划与管理]
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