基于网格靶标快速高精度摄像机标定方法

本文针对单摄像机成像特点,首先建立其实际成像数学模型,为快速高精度的标定摄像机参数,靶标采用平行网格线靶标,有效利用直线的平行性约束条件,可高效的求取目标点,此种方法先求解摄像机纵横比,然后利用参数分离的方法通过迭代求解其余模型参数,从而简化了求解过程,将标定结果与Tsai法相比较可知,标定精度相当。     

基于等边三角形的摄像机标定方法

利用摄影儿何中交比不变性的性质,从给定的n幅图像中捉取所需要的点坐标,求解出三纽两两正交的直线的消失点的坐标.根据光心与消失点的连线为直线的方向建立3n个方程,从中线性的求解出相机的内参数.实验证明该方法不需要特定的标定模板,具有一定的实用价值.     

摄像机径向畸变校正和内参估计的单图标定方法

提出了一种对摄像机的径向畸变进行校正和内参数估计的单图标定方法.拍摄一幅平面标定模板图像,提出若干条直线,拟合在单参数除法畸变模型下的圆弧参数,从而估计出径向畸变.对径向畸变进行校正后,利用标定模板点与经过校正后的图像点之间的对应关系,估计出单应性矩阵.在假定摄像机主点与畸变中心重合的条件下,线性地计算出摄像机焦距初值.以上述线性方法得到的结果为初值,进行非线性优化,最终得到准确的摄像机参数.超广角鱼眼相机和普通数码相机的实验结果表明,本文提出的算法实现简单、适用性广,结果准确,具有较强的实用性.     

一种摄像机自动标定方法的设计与实现

设计并实现了一种摄像机内外参数的自动标定方法：提出了一种无伪的标定模板图像角点的自动提取,以及与对应物理空间坐标的匹配算法;进而,以此结果作为标定基础数据,采用Tsai[Tsai R Y．A versatile cameraca libration technique for high-accuracy 3D machine vision metrology using offthe-shelf TV cameras and lenses[J]．IEEE Journal of Robotics and Automation RA,1987,3(4)：323-344．]的两级标定法,获取摄像机的内外参数;以LabVIEW为平台,开发了一个摄像机自动标定系统,并进行了实验验证。     

基于卡尔曼滤波的摄像机标定方法

本文提出了一种基于迭代扩展卡尔曼滤波的摄像机标定方法.将二维平面靶标图像上的特征点看作是匀速运动的点,以观测到的特征点图像坐标和对应世界坐标作为滤波器的输入,摄像机内外参数的估计值作为滤波器的输出,根据迭代扩展卡尔曼滤波算法得到摄像机内外参数的最优估计.通过仿真和真实实验,结果表明,对于有限数量的平面靶标标定图像数据,该算法具有较高的标定精度和较好的鲁棒性.     

基于双目摄像机的目标标定及校正方法研究

本文采用的是平行双目立体视觉机,主要目的是从摄像机获取的立体图像出发,根据两个摄像机之间的相对位置关系得到场景中物体的深度信息,以便实现运动人体的检测与识别。     

采用单幅圆柱体图像的摄像机标定

单幅圆柱体图像由于所包含的立体信息较少,传统的方法很难实现摄像机标定.根据透视投影理论中灭点的几何性质,计算出相机的内、外参数,以此实现相机标定.实验表明,此法易于操作,结果令人满意.     

一种摄像机自标定的线性方法

提出了一种基于空间共面直线从单幅图像进行摄像机自标定的线性方法.本方法结合工程应用实际,直接利用场景的直角信息,根据点的中心投影关系,推导直线的投影关系,基于平面上不平行的3条直线,由单幅图像线性的高精度的标定出摄像机内、外参数.算法用仿真实验和实拍图像都得到了精确、可靠的结果,在精度上明显优于基于共面点的算法.     

基于OpenCV的集装箱加强板焊接点定位技术

实现一种基于OpenCV的集装箱加强板焊接点的定位技术。首先对加强板的图像进行预处理,然后从处理后的二值图像中寻找轮廓,再利用Douglas-Peucker算法对轮廓进行多边形逼近,根据Shi-Tomasi算法提取角点的像素坐标,最后利用张正友标定法进行摄像机定标,并计算出对应的实际坐标。实验表明,采用此技术的焊接系统具有操作简单、焊接精度高、开发效率高等优点。     

用三线法标定车载摄像机的外部参数

根据摄像机透视投影原理,三条互不重合的平行线在图像平面上具有相同的消失点和不同的斜率。按照针孔成像模型,经过数学推导可以建立摄像机的外部参数与消失点和成像斜率之间的解析表达式,无需经过迭代和优化计算。实现过程只需要地面上有三条平行线,然后通过手工或自动的方式确定出这三条直线成像的交点和斜率,就可以标定出摄像机的外部参数。实验表明,该方法可以在不同环境下进行车载摄像机标定,方位角和俯仰角的标定误差小于百分之一弧度。     

一种显微图像测量系统的标定方法

提出了一种显微图像测量系统的标定方法。该方法通过同一对平行边缘在垂直和水平方向的两幅图像,计算水平比例因子;利用标定物直线边缘的图像,并运用优化的方法来计算成像系统的畸变系数和主点位置。在上述计算的基础上,利用量块来标定系统的放大倍数。标定过程所需的标定物为量规和带有平行刻线光学器件,如分辨率板等,因此方便实用。试验结果表明,该方法标定精度较高,标定后的实验装置的极限误差3σ为2.26μm。     

An efficient camera calibration and optimisation method based on orthogonal vanishing points

A more efficient camera calibration and optimisation method based on orthogonal vanishing points is proposed. After extracting corner points on the calibration images by using the Harris algorithm, some parallel lines are fitted via the least square method. The Levenberg–Marquard (L–M) algorithm is used to find out the optimum vanishing points. The intrinsic parameters are solved on the basis of the orthogonal vanishing point characters. The enhanced Tsai’s method is designed to solve the extrinsic parameters. The minimum residue optimisation function is introduced to calculate the distortion coefficients and optimise all parameters globally. The feasibility and efficiency of the proposed method is illustrated by an experimental study. The method can be used to obtain high precision calibration parameters without the need of sophisticated mechanical devices. It has great potential to calibration cameras in the field of computer vision, 3D measurement, etc.     

Camera calibration using a genetic algorithm

An autonomous robot will have to detect moving obstacles online before it can plan its collision-free path, while navigating in a dynamic environment. The robot collects information about the environment with the help of a camera and determines the inputs for its motion planner through image analysis. The present article deals with issues related to camera calibration and online image processing. The problem of camera calibration is treated as an optimization problem and solved using a genetic algorithm so as to achieve minimum distorted image plane error. The calibrated vision system is then utilized for the detection and identification of the objects by analysing the images collected at regular intervals. For image processing, five different operations, such as median filtering, thresholding, perimeter estimation, labelling and size filtering, have been carried out. To show the effectiveness of the developed camera-based vision system, inputs of the motion planner of a navigating robot are calculated for two different cases. It is observed that online detection of the shapes and configurations of the obstacles is possible by using the vision system developed.     

Novel method of calibration with restrictive constraints for stereo-vision system

Regarding the calibration of a stereo vision measurement system, this paper puts forward a new bundle adjustment algorithm based on the stereo vision camera calibration method. Multiple-view geometric constraints and a bundle adjustment algorithm are used to optimize the inner and outer parameters of the camera accurately. A fixed relative constraint relationship between cameras is introduced. We have improved the normal equation construction process of the traditional bundle adjustment method, so that each iteration process occurs just outside the parameters of two images that are taken by a camera that has been optimized to better integrate two cameras bound together as one camera. The relationship between the fixed relative constraints can effectively increase the number of superfluous observations of the adjustment system and optimize higher accuracy while reducing the dimension of the normal matrix; it means that each iteration will reduce the time required. Simulation and actual experimental results show the superior performance of the proposed approach in terms of robustness and accuracy, and our approach also can be extended to stereo-vision system with more than two cameras.     

适用于离焦状态相机的相位编码标定方法

现阶段通用的相机标定方法需要使用者提供准确的标定板特征点像素坐标。但对某些成像位置特殊的相机而言,一般标定物(如长宽在厘米级别的标定板)的使用范围在其清晰成像范围之外。使用这些相机拍摄一般标定物,只能得到离焦的模糊图像,无法准确提取特征点像素坐标。本文分析了光学系统离焦状态对基于正弦光栅的结构光(简称正弦结构光)相位的影响。利用正弦结构光相位与相机对焦状态无关的性质,提出了一种利用相移法正弦结构光编码的方法,对标定物上特征点进行相位编码,实现了相机在离焦状态下的标定。经过实验验证,标定结果焦距长度与真实值之间最大偏差为0.47%,最大像素重投影误差为0.17 pixels。该方法为具有特殊成像范围的相机的标定提供了一种解决方案。     

球幕点目标投影跟踪系统的精确标定方法

针对球幕点目标投影与跟踪系统中多个子系统相对位置关系探测复杂的问题,提出了一种适合现场测量的精确标定方法。将球幕作为世界坐标系,利用子系统对球幕球心标定,得到子系统在球幕坐标系下的坐标,从而实现目标点在子系统之间的坐标转换。研究了球幕球心标定原理及标定点投射方法,建立了球幕球心在标定系统坐标系下的高斯-马尔科夫(G-M)求解模型,仿真分析了影响标定误差的因素。结果表明,通过减小子系统到球心的距离和改进投射的标定点空间分布能够有效提高标定精度,最后提出基于整体最小二乘(TLS)的球幕标定方法。根据仿真结果,设计模拟球幕和标定器并完成实验,标定结果满足现场快速精确标定的要求。     

Analytical method for camera calibration from a single image with four coplanar control lines

An analytical method to calibrate a camera's extrinsic parameters and effective focal lengths is presented. We used a single image with four coplanar control lines. Unique solutions of the camera's extrinsic parameters and the two effective focal lengths are derived linearly and analytically. If the effective focal lengths are known, unique solutions of the extrinsic parameters can be derived more easily. Our method can easily be implemented and has better precision than the analogous method by use of control points. The results of simulated experiments are presented.     

工业机器人校准技术与补偿方法发展现状及趋势

工业机器人因具有自动化程度高、定位精度好等优势,已成为我国工业智能化的攻关方向之一,并将逐步替代人工,在智能制造领域发挥不可替代的作用.在使用过程中,造成工业机器人准确度下降的因素众多,将直接影响其在叶片研磨、高精度钻铆等高精尖领域中的应用.文章在总结工业机器人通用校准模型的基础上,分析了工业机器人校准技术与误差补偿方...