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针对工业上一些无法正对待测端面安装相机的直径测量场景,设计了一种由3个激光投线器、1个成像透镜及1个面阵CMOS相机组成的圆柱工件直径测量系统,放置于地面上倾斜投影并成像。搭建了测量系统,从图像中获得亚像素端点坐标,代入标定方程解算世界坐标,并通过几何模型计算待测直径。实验结果表明,该系统能在设计待测值附近准确测量工件的端面直径,测量精度在±0.1 mm以内,满足工业测量高精度要求。 相似文献
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车辆与轨道相对振动状态对轨道线形测量有重要影响;分析了传统检测车辆与轨道相对振动状态测量方法的缺陷,提出一种基于视觉的车轨相对振动状态测量方法,以轨道建立世界坐标系,以车体建立车体坐标系。考虑相机镜头畸变,建立相机非线性模型,基于机器人手眼方法标定相机与车体,求解相机内外参数。依据车体运动姿态特征,推导基于双目机器视觉的车辆运动姿态偏移补偿计算方法;运用实验平台设计验证实验,通过计算所得的车体振动位移与真实值高度吻合,随着车速增加振动位移误差也随之增大,验证了该方法的正确性和可行性;提供一种车辆与轨道相对振动状态测量方法。 相似文献
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车辆轮对踏面缺陷的光电检测方法研究 总被引:1,自引:0,他引:1
铁路车辆轮对踏面的擦伤与剥离是车辆在运行过程中形成的一种常见的不规则表面缺陷,是轮对检修过程中必须检测的一个项目。提出了一种利用光电技术非接触测量此表面缺陷的方法。该方法在轮对旋转条件下,用精密激光位移传感器对踏面进行快速扫描,采集值经处理后被转换为数字图像,再通过图像处理识别是否存在表面缺陷。必要时通过对缺陷部位的往复扫描,更准确识别出擦伤与剥离是否超出段修限度。该方法可有效检测出踏面缺陷,重复性好,可满足车辆段修现场使用要求。 相似文献
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条纹投影轮廓术由于具有速度快、精度高、对环境光照和表面纹理具有鲁棒性等优点,在许多领域得到了广泛应用。但是,它容易受到高动态范围(high dynamic range, HDR)对象的影响。因此提出了一种快速计算最佳投影亮度的方法。通过求解相机与投影仪之间的响应关系,结合所提出的一个简便的投影亮度确定方法,可以得到测量所需要的投影亮度。再基于所提出的图像融合算法融合求得的各个亮度下的原始图片,从而获得高质量的融合图片,实现对HDR物体的高精度的三维重构。相较于传统方法,无需盲目投射和拍摄大量图片或计算复杂的单应性矩阵,仅需要投影一张均匀白光至被测物体,即可快速求解出相机和投影仪之间的响应函数,从而获得所需的投影亮度,使得测量速度有极大的提升。 相似文献
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鉴于透视投影模型在长焦相机标定过程中存在过参数化的问题,采用仿射近似投影模型对长焦相机成像过程进行建模,并提出了基于仿射近似投影模型的长焦相机标定方法。首先,深入分析了仿射投影位姿模糊的形成机制,在此基础上详细推导了仿射近似投影下基于平面模板的长焦相机内外参数解算方法;然后,基于透视投影模型,以重投影像点残差平方和最小为目标函数,对内外参数初值进行优化求精;最后,针对仿射投影模型的位姿模糊,在平面标定模板基础上附加微凸圆柱标志。仿真和实际实验结果显示,所提出的长焦相机标定方法有效可行,在实验室环境下重建平面目标的离面中误差优于0.02 mm。 相似文献
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条纹投影三维测量技术的检测精度依赖于绝对相位与深度关系的标定过程,传统的标定方法步骤复杂、用时较长,在双目测量系统中对左右相机分别标定时尤为明显。因此设计一种基于立体靶标的标定方法,靶标由两个平面组成,各个靶标平面上附着规格已知的图案,平面连接处用特殊图案标识,用于区分左右两面。立体标靶实现双目测量系统相机外部参数与相位-深度的同时标定,将标定时间减少了一半,简化了标定流程;经过实验验证,利用立体标靶可以精确地进行深度(Z)以及横向(XY)的标定,实测误差小于0.053毫米,方法在双目乃至多节点三维测量系统的标定过程中具有应用价值,增加标定效率同时可避免累计误差产生。 相似文献
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为了抵抗满载时的负载,轨道车辆制造时车体底座会保留一定向上的挠曲变形,这就要求在进行铝蜂窝板和地板胶铺设前对车体底座表面面型进行测量。提出了一种基于点状目标图像测量原理的车体底座面型测量方法,该方法用CMOS相机对车体底座上的4个LED目标进行图像测量,这4个LED形成关联多目标点。先对CMOS相机采集到的LED目标图像用均值滤波、动态阈值二值化处理和轮廓提取的方法进行预处理,再通过灰度质心法,提取出多个光斑的位置。通过判断各光斑的位置和大小,排除可能存在的伪目标点或遮拦,根据提取到的光斑数量的不同,采用不同的参考点进行比较。在任意一个LED目标被遮挡时,算法仍能有效地解出被测LED目标中心位置。实验结果表明,LED靶标中心提取的最大偏差小于0.06 mm,完全能满足车体底座面型测量的需求。 相似文献
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前景检测的精确程度是交叉路口车辆检测的重要因素,传统的基于背景建模的前景检测方法存在拖影现象,并且通常难以分辨出无牌车辆,针对上述问题,提出一种融合ViBe与帧差法的前景检测算法,并在此基础上结合车牌检测算法来检测场景当中的车辆。首先,结合帧差法和ViBe算法对背景像素点的判定结果,采用不同更新因子更新背景模型,其次,使用一种多条件过滤车牌检测算法定位运动区域当中车牌,最后,以检测到的车牌中心为锚点,定位出最终车牌区域。实验结果表明,该前景检测算法可有效应对交叉路口场景下的前景检测的拖影现象,同时车辆检测算法可以准确检测出进入场景时的车辆,并分辨出无牌车辆。 相似文献
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Vehicle detection plays a vital role in the design of Automatic Driving System (ADS), which has achieved remarkable improvements in recent years. However, vehicle detection in night scenes still has considerable challenges for the reason that the vehicle features are not obvious and are easily affected by complex road lighting or lights from vehicles. In this paper, a high-accuracy vehicle detection algorithm is proposed to detect vehicles in night scenes. Firstly, an improved Generative Adversarial Network (GAN), named Attentive GAN, is used to enhance the vehicle features of nighttime images. Then, with the purpose of achieving a higher detection accuracy, a multiple local regression is employed in the regression branch, which predicts multiple bounding box offsets. An improved Region of Interest (RoI) pooling method is used to get distinguishing features in a classification branch based on Faster Region-based Convolutional Neural Network (R-CNN). Cross entropy loss is introduced to improve the accuracy of classification branch. The proposed method is examined with the proposed dataset, which is composed of the selected nighttime images from BDD-100k dataset (Berkeley Diverse Driving Database, including 100,000 images). Compared with a series of state-of-the-art detectors, the experiments demonstrate that the proposed algorithm can effectively contribute to vehicle detection accuracy in nighttime. 相似文献
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对近红外钢轨磨耗检测中实时图像处理方法进行了研究.在断面磨耗检测中,要获取较高精度的磨耗数值,起始点(或称坐标基准)的定位必须准确且误差小.考虑到标准钢轨轨形和实际钢轨磨耗情况,得出了起始点两种可行的定位方式,并就其中的一种用编程实现,仿真处理效果良好,所获取的两关键点的磨耗数值与实测值吻合较好.为了进行实采钢轨轨形与标准轨形的模板比较,讨论了钢轨断面图像的细化问题.这里并没有采用通常的细化算法,而是先利用Roberts算子进行图像的边缘检测,再抽取出光带中心线,大大减少了运算量,提高了运算速度,同时也满足了对轨形细化的要求.断面图像的起始点定位与轨形细化兼顾了处理精度和速度的要求,满足了本系统实时检测的要求. 相似文献
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Vehicle detection is an essential part of an intelligent traffic system, which is an important research field in drone application. Because unmanned aerial vehicles (UAVs) are rarely configured with stable camera platforms, aerial images are easily blurred. There is a challenge for detectors to accurately locate vehicles in blurred images in the target detection process. To improve the detection performance of blurred images, an end-to-end adaptive vehicle detection algorithm (DCNet) for drones is proposed in this article. First, the clarity evaluation module is used to determine adaptively whether the input image is a blurred image using improved information entropy. An improved GAN called Drone-GAN is proposed to enhance the vehicle features of blurred images. Extensive experiments were performed, the results of which show that the proposed method can detect both blurred and clear images well in poor environments (complex illumination and occlusion). The detector proposed achieves larger gains compared with SOTA detectors. The proposed method can enhance the vehicle feature details in blurred images effectively and improve the detection accuracy of blurred aerial images, which shows good performance with regard to resistance to shake. 相似文献
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In this paper, we provide the results of multi-passenger occupancy detection inside a vehicle obtained using a single-channel frequency-modulated continuous-wave radar. The physiological characteristics of the radar signal are analyzed in a time-frequency spectrum, and features are proposed based on these characteristics for multi-passenger occupancy detection. After clutter removal is applied, the spectral power and Wiener entropy are proposed as features to quantify physiological movements arising from breathing and heartbeat. Using the average means of both the power and Wiener entropy at seats 1 and 2, the feature distributions are expressed, and classification is performed. The multi-passenger occupancy detection performance is evaluated using linear discriminant analysis and maximum likelihood estimation. The results indicate that the proposed power and Wiener entropy are effective features for multi-passenger occupancy detection. 相似文献