技术领域technical field
本发明涉及一种结构光三维视觉检测技术，特别是涉及一种激光视觉轮廓测量系统快速标定方法及其立体靶标。The invention relates to a structured light three-dimensional vision inspection technology, in particular to a rapid calibration method for a laser vision contour measurement system and a three-dimensional target.
背景技术Background technique
结构光三维视觉测量技术，具有视觉测量的非接触、速度快、自动化程度高，柔性好等优点。结构光三维视觉基于光学三角法原理，通过计算采集图像的各种光模式特征点的偏移信息反算出被测物体的表面轮廓。光学投射器投射确定的光模式，使得结构光图像信息易于提取，因而测量精度较高，广泛应用于各种工业产品的在线检测。Structured light three-dimensional visual measurement technology has the advantages of non-contact visual measurement, high speed, high degree of automation, and good flexibility. Structured light 3D vision is based on the principle of optical triangulation, and calculates the surface profile of the measured object by calculating the offset information of various light mode feature points in the collected images. The optical projector projects a certain light pattern, which makes the structured light image information easy to extract, so the measurement accuracy is high, and it is widely used in the online detection of various industrial products.
典型线结构光视觉传感器，由一个线结构光激光器和配套的摄像机组成。通过激光器垂直入射被测物表面，摄像机倾斜拍摄的方式，获取激光平面与被测物表面相交激光光条图像。通过视觉测量模型，将激光光条中心的图像坐标转换为被测物表面轮廓的二维坐标。当被测物运动或线结构光传感器做相对运动时，就能得到被测物表面的三维形貌。但是单套视觉传感器视场有限，往往只能获取被测物表面某一局部的轮廓信息，无法对被测物表面轮廓360°范围进行全方位测量。A typical line structured light vision sensor consists of a line structured light laser and a matching camera. The laser light bar image where the laser plane intersects the surface of the measured object is acquired through the way that the laser is incident vertically on the surface of the measured object and the camera is tilted to shoot. Through the visual measurement model, the image coordinates of the center of the laser light bar are converted into the two-dimensional coordinates of the surface profile of the measured object. When the measured object moves or the line structured light sensor makes relative motion, the three-dimensional topography of the surface of the measured object can be obtained. However, a single set of vision sensors has a limited field of view, and often can only obtain the contour information of a certain part of the surface of the measured object, and cannot perform all-round measurement of the 360° range of the surface contour of the measured object.
发明内容Contents of the invention
为了克服上述现有技术，本发明提出了一种激光视觉轮廓测量系统及其快速标定方法及立体靶标，该系统采用四套线结构光传感器同时测量的方式，能够实现对被测物表面轮廓全方位的测量；同时为解决由于引入多传感器而带来的标定的复杂性和测量坐标系统一问题，本方案还结合Zhang摄像机标定过程，设计了一种新型LED立体靶标，并根据靶标特性，设计了轮廓传感器全局统一标定方法；以及，提出一种激光视觉轮廓测量系统，该系统采用LED立体靶标首先实现快速标定，然后实现被测物三维轮廓的准确测量方法。In order to overcome the above-mentioned prior art, the present invention proposes a laser vision contour measurement system and its rapid calibration method and three-dimensional target. Orientation measurement; at the same time, in order to solve the problem of calibration complexity and measurement coordinate system caused by the introduction of multiple sensors, this program also designed a new LED three-dimensional target based on the calibration process of the Zhang camera, and according to the target characteristics, design A global unified calibration method for contour sensors is proposed; and a laser vision contour measurement system is proposed, which uses LED stereoscopic targets to achieve rapid calibration first, and then realizes an accurate measurement method for the three-dimensional contour of the measured object.
本发明提出了一种立体靶标，所述立体靶标为一中空立方体结构，每个靶标面均为边长120mm的正方形，每个靶标面上设置有特征圆孔，所述特征圆孔大小相同，彼此之间的位置关系相同。The present invention proposes a three-dimensional target, the three-dimensional target is a hollow cubic structure, each target surface is a square with a side length of 120 mm, each target surface is provided with a characteristic circular hole, and the characteristic circular holes have the same size, The positional relationship between each other is the same.
本发明还提出了一种激光视觉轮廓测量系统，包括测量部分和标定部分，所述测量部分包括四个一字线状激光器和四个CCD摄像机，其中每个激光器与CCD摄像机组成一个传感器，一共组成四个所述传感器并分别设置于四个机械架上，各传感器环绕在被测物周围，四个一字线状激光器投射光能全部覆盖一个被测物截面且都在对应摄像机视场范围内；所述标定部分包括一立体靶标，所述立体靶标为一中空立方体结构，每个靶标面均为边长120mm的正方形，每个靶标面上设置有特征圆孔，所述特征圆孔大小相同，彼此之间的位置关系相同；所述立体靶标每个靶标面上的特征圆孔均由相同颜色LED点亮；The present invention also proposes a laser vision profile measurement system, including a measurement part and a calibration part, the measurement part includes four inline lasers and four CCD cameras, wherein each laser and the CCD camera form a sensor, a total of Four of the above-mentioned sensors are composed and arranged on four mechanical frames respectively. Each sensor surrounds the object to be measured, and the light energy projected by the four inline lasers all cover a cross-section of the object to be measured and are all within the field of view of the corresponding camera. Inside; the calibration part includes a three-dimensional target, the three-dimensional target is a hollow cubic structure, each target surface is a square with a side length of 120mm, each target surface is provided with a characteristic circular hole, the size of the characteristic circular hole is The same, the positional relationship between each other is the same; the characteristic circular holes on each target surface of the three-dimensional target are lit by LEDs of the same color;
激光投射到被测物表面之后，靶标面上的光条受被测物表面反射光的调制，对应CCD摄像机拍摄被测物的三维图像，图像中的光条包含了被测物表面的三维信息，将被测物的三维图像经由以太网传送至计算机，由计算机利用标定得来的各传感器参数等计算得出被测物截面三维数据。After the laser is projected onto the surface of the measured object, the light strips on the target surface are modulated by the reflected light from the surface of the measured object, corresponding to the CCD camera to capture the three-dimensional image of the measured object, and the light strips in the image contain the three-dimensional information of the measured object surface , the three-dimensional image of the measured object is transmitted to the computer via Ethernet, and the computer uses the calibrated sensor parameters to calculate the three-dimensional data of the cross-section of the measured object.
本发明再提出了一种激光视觉轮廓测量系统测量方法，该方法包括以下步骤：The present invention further proposes a measurement method of a laser vision contour measurement system, the method comprising the following steps:
一种激光视觉轮廓测量系统测量方法，其特征在于，该方法包括以下步骤：A laser vision profilometer measurement method, characterized in that the method comprises the following steps:
步骤1、打开激光器，将立体靶标按照Zhang标定方法摆放于10个不同位置，且每个摄像机对应于靶标面及各靶标面上的光条在相应摄像机视场范围内且成像清晰；利用CCD摄像机采集标定图，对标定图进行处理计算，计算过程依顺序包括：特征圆孔边缘提取、椭圆拟合、椭圆中心特征点提取、摄像机标定、光条中心提取、光平面拟合，以及进行坐标系统一；Step 1. Turn on the laser, place the three-dimensional target in 10 different positions according to the Zhang calibration method, and each camera corresponds to the target surface and the light strips on each target surface are within the corresponding camera field of view and the image is clear; use CCD The camera collects the calibration map, and the calibration map is processed and calculated. The calculation process includes in order: feature hole edge extraction, ellipse fitting, ellipse center feature point extraction, camera calibration, light strip center extraction, light plane fitting, and coordinates. system one;
步骤2、通过提取光条中心特征点，结合Zhang摄像机模型，反算出被测物体截面轮廓尺寸，具体处理如下：Step 2. By extracting the central feature point of the light strip and combining the Zhang camera model, the cross-sectional contour size of the measured object is calculated inversely. The specific processing is as follows:
首先通过摄像机坐标系下的坐标值(xc,yc,zc)和光平面方程约束得到图像光条中心点(u,v)和摄像机坐标系下点坐标(xc,yc,zc)之间一一对应关系，建立起从二维像素坐标到摄像机坐标系坐标的一一映射关系；然后将摄像机坐标系下的点通过坐标系变换，即利用标定得到的旋转矩阵和平移矩阵，转换得到测量坐标系下被测物的截面轮廓三维坐标，其中：First, through the coordinate values (xc , yc , zc ) in the camera coordinate system and the light plane equation constraints, the center point (u, v) of the image light strip and the coordinates of the point in the camera coordinate system (xc , yc , zc ) to establish a one-to-one mapping relationship from two-dimensional pixel coordinates to camera coordinate system coordinates; Transform to obtain the three-dimensional coordinates of the cross-sectional profile of the measured object in the measurement coordinate system, where:
摄像机坐标系下光平面方程约束为：The light plane equation constraint in the camera coordinate system is:
axc+byc+czc+d＝0axc +byc +czc +d＝0
图像上某点在摄像机坐标系下的坐标值(xc,yc,zc)为：The coordinate values (xc , yc , zc ) of a point on the image in the camera coordinate system are:
与现有技术相比，本发明利用该LED立体靶标，在标定过程中只需要在摄像机视场范围中把靶标随意摆放几个位置即可，操作简单，可以迅速便捷的完成对传感器全局统一标定，并能够应用于工业现场；对于需要全方位测量物体截面轮廓的场合，如对各种机械零件截面轮廓尺寸在线检测，本方案有较好的技术优势。Compared with the prior art, the present invention uses the LED three-dimensional target, and only needs to place the target in several positions in the field of view of the camera during the calibration process. The operation is simple, and the global unification of the sensor can be quickly and conveniently completed. Calibration, and can be applied to industrial sites; for occasions that need to measure the cross-sectional profile of objects in an all-round way, such as online detection of the cross-sectional profile dimensions of various mechanical parts, this solution has better technical advantages.
附图说明Description of drawings
图1为本发明的激光视觉轮廓测量系统的结构示意图；其中：1-4、CCD摄像机；5-8、一字线状激光器；9-12、机械架；Fig. 1 is the structural representation of laser vision profilometer system of the present invention; Wherein: 1-4, CCD camera; 5-8, linear laser device; 9-12, mechanical frame;
图2为LED立体靶标；13、激光条；14、靶标面；15、特征孔；16、坐标系一；17、坐标系二；Fig. 2 is LED three-dimensional target; 13, laser bar; 14, target surface; 15, feature hole; 16, coordinate system one; 17, coordinate system two;
图3为靶标特征提取；(a)采集的靶标图像；(b)椭圆拟合，特征提取；Fig. 3 is target feature extraction; (a) target image collected; (b) ellipse fitting, feature extraction;
图4为不同直径塔轮层轮廓测量误差图。Figure 4 is a diagram of the measurement error of the profile of the cone layer with different diameters.
具体实施方式Detailed ways
下面结合附图和具体实施方式对本发明进行详细说明，但本发明的实施范围并不局限于此。The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments, but the implementation scope of the present invention is not limited thereto.
为了解决单套视觉传感器视场有限，无法全方位测量被测物表面轮廓的问题，本发明提出了一套激光视觉轮廓测量系统，结合Zhang摄像机标定过程，以及设计了一种新型LED立体靶标，并根据靶标特性，设计了可应用于工业现场的快速统一标定方法。In order to solve the problem that a single set of visual sensor has a limited field of view and cannot measure the surface profile of the measured object in an all-round way, the present invention proposes a set of laser visual profile measurement system, combined with the Zhang camera calibration process, and designed a new type of LED three-dimensional target, And according to the characteristics of the target, a fast and unified calibration method that can be applied to industrial sites is designed.
一、激光视觉轮廓测量系统1. Laser Vision Contour Measurement System
如图1所示，为本发明计的激光视觉轮廓测量系统结构图。As shown in Figure 1, it is a structural diagram of the laser vision contour measurement system of the present invention.
系统包含四个一字线状激光器和四个CCD摄像机及其它机械结构，其中每个激光器与CCD摄像机组成一个传感器，各传感器环绕在被测物周围，具有一定相对位置关系，激光器发散角和摄像机视场角应适当大，以满足四个激光器投射光能全部覆盖一个被测物截面且都在对应摄像机视场范围内。用于安装摄像机的机械架可以根据需要调节摄像机高度，摄像机固定部分具有一微小旋转结构用以调整摄像机倾角，根据需要可以对系统进行方便快捷的调节。The system includes four linear lasers, four CCD cameras and other mechanical structures, where each laser and CCD camera form a sensor, each sensor surrounds the object to be measured, has a certain relative positional relationship, the divergence angle of the laser and the camera The field of view angle should be appropriately large so that the projected light energy of the four lasers can all cover a section of the measured object and be within the field of view of the corresponding camera. The mechanical frame used to install the camera can adjust the height of the camera according to the needs, and the fixed part of the camera has a small rotating structure to adjust the tilt angle of the camera, and the system can be adjusted conveniently and quickly according to the needs.
激光投射到被测物表面之后，光条受被测物表面情况的调制，对应CCD摄像机拍摄图像，图像中的光条就包含了被测物表面的三维信息，将图像经由以太网传送至计算机，由计算机利用标定得来的各传感器参数等可计算得出被测物截面三维数据。同时，四个轮廓传感器的测量数据，需通过摄像机标定参数统一于同一测量坐标系下，才能完整显示某一时刻被测物截面轮廓。After the laser is projected onto the surface of the measured object, the light strip is modulated by the surface condition of the measured object, corresponding to the image taken by the CCD camera, the light strip in the image contains the three-dimensional information of the surface of the measured object, and the image is transmitted to the computer via Ethernet , the three-dimensional data of the cross-section of the measured object can be calculated by the computer using the sensor parameters obtained through calibration. At the same time, the measurement data of the four profile sensors need to be unified in the same measurement coordinate system through the camera calibration parameters, so as to fully display the cross-sectional profile of the measured object at a certain moment.
2、传感器标定及全局统一2. Sensor calibration and global unification
(1)Zhang摄像机透视变换模型(1) Zhang camera perspective transformation model
Zhang模型一般以摄像机坐标系为空间坐标系，设空间某一点P在摄像机坐标系下的坐标为(xc,yc,zc)，在最终物空间坐标系中坐标为(xw,yw,zw)，则该模型的坐标系转换关系如下：The Zhang model generally takes the camera coordinate system as the space coordinate system. Let the coordinates of a certain point P in the space be (xc , yc , zc ) in the camera coordinate system, and the coordinates in the final object space coordinate system be (xw , yw , zw ), then the transformation relation of the coordinate system of the model is as follows:
上式中，矩阵A为摄像机内参数矩阵，R、T为摄像机外参数矩阵。但是由上式可以看到，直接利用(u,v)并不能得出(xc,yc,zc)的唯一解，为此本发明引入摄像机坐标系下光平面方程约束：In the above formula, the matrix A is the internal parameter matrix of the camera, and R and T are the external parameter matrices of the camera. However, it can be seen from the above formula that the unique solution of (xc , yc , zc ) cannot be obtained directly by using (u, v), so the present invention introduces the constraint of the light plane equation in the camera coordinate system:
axc+byc+czc+d＝0 (2)axc +byc +czc +d＝0 (2)
这样就能建立起从二维像素坐标到摄像机坐标系坐标的一一映射关系。系统标定得到摄像机内外参数，k1、k2、p1、p2为摄像机径向畸变系数和切向畸变系数，以此对实际图像坐标(u1,v1)进行畸变校正，获取理想图像坐标(u,v)，由(u,v)及光平面参数和摄像机内外参数可以得到图像上某点在摄像机坐标系下的坐标值(xc,yc,zc)：In this way, a one-to-one mapping relationship from two-dimensional pixel coordinates to camera coordinate system coordinates can be established. The internal and external parameters of the camera are obtained through system calibration, k1 , k2 , p1 , and p2 are the radial and tangential distortion coefficients of the camera, so as to correct the distortion of the actual image coordinates (u1 , v1 ) and obtain an ideal image Coordinates (u, v), the coordinates (xc , yc , zc ) of a point on the image in the camera coordinate system can be obtained from (u, v) and the light plane parameters and camera internal and external parameters:
通过提取光条中心特征点，结合Zhang摄像机模型，反算出被测物体截面轮廓尺寸，方法如下：By extracting the central feature point of the light strip, combined with the Zhang camera model, the cross-sectional outline size of the measured object is calculated inversely, as follows:
首先通过公式(3)和光平面约束(2)可以得到图像光条中心点(u,v)和摄像机坐标系下点坐标(xc,yc,zc)之间一一对应关系，然后将摄像机坐标系下的点通过坐标系变换，即利用标定得到的旋转矩阵和平移矩阵，转换得到测量坐标系下被测物的截面轮廓三维坐标。First, the one-to-one correspondence between the center point (u, v) of the image light strip and the point coordinates (xc , yc , zc ) in the camera coordinate system can be obtained through the formula (3) and the light plane constraint (2), and then The points in the camera coordinate system are transformed through the coordinate system, that is, the rotation matrix and translation matrix obtained by calibration are used to convert the three-dimensional coordinates of the cross-sectional profile of the measured object in the measurement coordinate system.
(2)立体靶标(2) Stereo target
如图2所示，为本发明所设计的LED立体靶标。As shown in Figure 2, it is the LED three-dimensional target designed by the present invention.
该靶标是一中空立方体，每个靶标面均为边长120mm的正方形，每个靶标面上特征圆孔大小相同，位置关系相同，通过LED灯点亮各个特征圆孔，能够增强对比度，易于特征点的提取。系统标定采用Zhang标定方法，进行标定时只需要在摄像机视场范围内将靶标随意摆放几个位置，标定过程方便快捷，易应用于工业现场。The target is a hollow cube, and each target surface is a square with a side length of 120mm. The characteristic circular holes on each target surface have the same size and positional relationship. Lighting each characteristic circular hole with LED lights can enhance the contrast and facilitate features point extraction. The system calibration adopts the Zhang calibration method. When performing calibration, the target only needs to be randomly placed in several positions within the field of view of the camera. The calibration process is convenient and fast, and it is easy to apply to industrial sites.
(3)标定方法(3) Calibration method
如图2所示，立体靶标每个靶标面上的特征圆孔均由相同颜色LED点亮。各靶标面上特征圆孔分布均匀，在各个靶标面上建立的靶标面坐标系Owi-XwiYwiZwi(i＝1,2,3,4)，分布如图2所示，沿逆时针分布。系统以Ow1-Xw1Yw1Zw1为第一靶标面坐标系(见图2所示的白色坐标系)，各靶标面坐标系均以中心圆圆心为原点，右手水平方向为X轴正向，竖直向下为Y轴正向，垂直靶标面向里为Z轴正向。As shown in Figure 2, the characteristic circular holes on each target surface of the three-dimensional target are lit by LEDs of the same color. The characteristic circular holes on each target surface are evenly distributed, and the target surface coordinate system Owi -Xwi Ywi Zwi (i=1,2,3,4) established on each target surface is distributed as shown in Figure 2. Distributed counterclockwise. The system takes Ow1 -Xw1 Yw1 Zw1 as the first target surface coordinate system (see the white coordinate system shown in Figure 2), each target surface coordinate system takes the center of the center circle as the origin, and the horizontal direction of the right hand is the positive X axis. Direction, vertically downward is the positive direction of the Y axis, and vertical target faces inwards is the positive direction of the Z axis.
进行标定时，打开激光器并将靶标按照Zhang标定方法摆放10个不同位置，但需要保证每个摄像机对应靶标面及各光条在相应摄像机视场范围内且成像要清晰，如图3(a)所示。对标定图进行处理，提取光条中心，筛选轮廓，对靶标特征圆进行椭圆拟合以求取椭圆中心，得到靶标面上每个特征圆孔圆心在计算机图像坐标系里的坐标Iuv，根据标定图中任意两特征点之间的像素距离大小可以确定每个靶标面的中心圆，之后找出距离中心圆最近的四个特征圆，根据这四个特征圆和中心圆之间相对位置关系即可确定靶标面上其他特征圆的拓扑关系，如图3(b)所示。由此得出各个特征点在对应靶标面坐标系里的坐标(xwi,ywi,zwi)。将Iuv和(xwi,ywi,zwi)代入标定函数获得每个摄像机的内参数ki1、ki2、pi1、pi2、fxi、fyi、(u0i,v0i)、dxi、dyi和外参数Rij、Tij。其中i＝1,2,3,4代表第几号摄像机，j代表第几个标定位置。(其中，ki1、ki2为镜头径向畸变参数，pi1、pi2为镜头切向畸变参数，fxi、fyi为镜头焦距在图像横纵坐标方向上的归一化焦距，(u0i,v0i)为光轴中心与图像的交点即图像中心，dxi、dyi为图像横纵两个方向上相邻像素中心间间距Rij为旋转矩阵，Tij为平移矩阵)When performing calibration, turn on the laser and place the target in 10 different positions according to Zhang’s calibration method, but it is necessary to ensure that the corresponding target surface and each light bar of each camera are within the corresponding camera’s field of view and the imaging must be clear, as shown in Figure 3 (a ) shown. Process the calibration map, extract the center of the light bar, screen the contour, and perform ellipse fitting on the target characteristic circle to obtain the center of the ellipse, and obtain the coordinate Iuv of the center of each characteristic circular hole on the target surface in the computer image coordinate system, according to The pixel distance between any two feature points in the calibration map can determine the center circle of each target surface, and then find the four feature circles closest to the center circle, according to the relative positional relationship between the four feature circles and the center circle Then the topological relationship of other feature circles on the target surface can be determined, as shown in Fig. 3(b). From this, the coordinates (xwi , ywi , zwi ) of each feature point in the corresponding target surface coordinate system are obtained. Substitute Iuv and (xwi , ywi , zwi ) into the calibration function to obtain the internal parameters ki1 , ki2 , pi1 , pi2 , fxi , fyi , (u0 i,v0i ) of each camera , dxi , dyi and external parameters Rij , Tij . Among them, i=1, 2, 3, 4 represent the number of the camera, and j represents the calibration position of the number. (wherein, ki1 and ki2 are radial distortion parameters of the lens, pi1 and pi2 are tangential distortion parameters of the lens, fxi and fyi are normalized focal lengths of the focal length of the lens in the direction of the horizontal and vertical coordinates of the image, (u0 i, v0i ) is the intersection point between the center of the optical axis and the image, that is, the center of the image, dxi , dyi are the distances between adjacent pixel centers in the horizontal and vertical directions of the image, Rij is the rotation matrix, and Tij is the translation matrix)
设每幅标定图像的旋转矩阵Rij的第三列为(r3ij,r6ij,r9ij)T，以它为当前标定位置靶标面法向量，以该标定图的平移向量Tij(t1ij,t2ij,t3ij)T为靶标面原点在对应摄像机坐标系中坐标，则可得到该位置处靶标面在对应摄像机坐标系下的方程：Let the third column of the rotation matrix Rij of each calibration image be (r3ij ,r6ij ,r9ij )T , take it as the normal vector of the target surface at the current calibration position, and use the translation vector Tij (t1ij ,t2ij ,t3ij )T is the coordinates of the origin of the target surface in the corresponding camera coordinate system, then the equation of the target surface at this position in the corresponding camera coordinate system can be obtained:
r3ij·xcij+r6ij·ycij+r9ij·zcij＝r3ij·t1ij+r6ij·t2ij+r9ij·t3ij (4)r3ij xcij +r6ij ycij +r9ij zcij ＝r3ij t1ij +r6ij t2ij +r9ij t3ij (4)
设标定图中光条中心某点的图像坐标为(u′ij,v′ij)，对(u′ij,v′ij)去畸变处理后得到矫正后光条中心该点图像坐标(uij,vij)，利用(uij,vij)和公式(1)及摄像机坐标系测量模型可以计算得到每幅标定图中光条中心各点在对应摄像机坐标系中的坐标。标定时靶标摆放了j个不同位置，这样对每个激光器来说可以得到在同一光平面上的j条光条中心线上点在对应摄像机坐标系中坐标，对这些点进行主元分析法空间平面拟合，可以得到每个激光器投射光平面在对应摄像机坐标系下的方程。Set the image coordinates of a point in the center of the light bar in the calibration image as (u′ij , v′ij ), and after de-distorting (u′ij , v′ij ), the corrected image coordinates of the point in the center of the light bar (uij ,vij ), using (uij ,vij ) and formula (1) and the camera coordinate system measurement model can be used to calculate the coordinates of each point in the center of the light bar in each calibration map in the corresponding camera coordinate system. The target is placed in j different positions during calibration, so that for each laser, the coordinates of the points on the centerline of j light strips on the same light plane in the corresponding camera coordinate system can be obtained, and the principal component analysis method is performed on these points Spatial plane fitting can obtain the equation of each laser projected light plane in the corresponding camera coordinate system.
(4)坐标系统一(4) Coordinate system one
坐标系之间的转换可以通过两坐标系之间的旋转矩阵R和平移矩阵T来完成。根据立体靶标设计，四个靶标面之间具有严格的几何关系，它们中相邻两个靶标面相互垂直，每个靶标面上LED分布相同，因此在不考虑Yw轴方向时，Ow1-Xw1Yw1Zw1(i＝1,2,3,4)在同一平面里。设Rk1、Tk1为在靶标第一个标定位置时，第k(k＝2、3、4)靶标坐标系到坐标系Ow1-Xw1Yw1Zw1转换时的旋转矩阵和平移向量，由靶标面间几何关系可知:The transformation between the coordinate systems can be done through the rotation matrix R and the translation matrix T between the two coordinate systems. According to the three-dimensional target design, there is a strict geometric relationship between the four target surfaces, and the two adjacent target surfaces are perpendicular to each other, and the distribution of LEDs on each target surface is the same, so when the direction of the Yw axis is not considered, Ow1 - Xw1 Yw1 Zw1 (i=1, 2, 3, 4) are in the same plane. Let Rk1 and Tk1 be the rotation matrix and translation vector when the kth (k=2, 3, 4) target coordinate system is converted to the coordinate system Ow1 -Xw1 Yw1 Zw1 at the first calibration position of the target , it can be known from the geometric relationship between the target surfaces:
由此通过Rk1、Tk1(k＝2,3,4)可以计算得出被测物截面轮廓在在坐标系Ow1-Xw1Yw1Zw1下的坐标，到此完成了对整个系统的标定及测量坐标系的全局统一。From this, the coordinates of the cross-sectional profile of the measured object in the coordinate system Ow1 -Xw1 Yw1 Zw1 can be calculated through Rk1 and Tk1 (k=2,3,4). The global unification of calibration and measurement coordinate system.
最佳实施方式举例：根据测量范围，按照图2所示设计符合视场范围的靶标。然后按照图1所示系统结构搭建对应的测量系统。根据提出的标定方法，对采集的图像进行处理计算，按下列过程顺序完成：特征圆孔边缘提取，椭圆拟合，椭圆中心特征点提取，摄像机标定，光条中心提取，光平面拟合，坐标系统一，即可完成整个系统的标定。测量时，通过提取光条中心特征点，结合Zhang摄像机模型即可反算出被测物体截面轮廓尺寸。An example of the best implementation mode: according to the measurement range, design a target that fits the field of view as shown in Figure 2 . Then build the corresponding measurement system according to the system structure shown in Figure 1. According to the proposed calibration method, the collected images are processed and calculated in the following order: feature hole edge extraction, ellipse fitting, ellipse center feature point extraction, camera calibration, light strip center extraction, light plane fitting, coordinates System 1 can complete the calibration of the entire system. During measurement, by extracting the central feature point of the light strip, combined with the Zhang camera model, the cross-sectional profile size of the measured object can be calculated inversely.
通过本方案，针对不同标称直径塔轮截面轮廓进行了测量，测量误差如图4所示。可以看出本方案具有较高的稳定性和可靠性，在测量范围内系统精度能够达到0.2mm。Through this scheme, the cross-sectional profile of cone pulleys with different nominal diameters is measured, and the measurement error is shown in Figure 4. It can be seen that this scheme has high stability and reliability, and the system accuracy can reach 0.2mm within the measurement range.
尽管上面结合图对本发明进行了描述，但是本发明并不局限于上述的具体实施方式，上述的具体实施方式仅仅是示意性的，而不是限制性的，本领域的普通技术人员在本发明的启示下，在不脱离本发明宗旨的情况下，还可以作出很多变形，这些均属于本发明的保护之内。Although the present invention has been described above in conjunction with the drawings, the present invention is not limited to the above-mentioned specific embodiments, and the above-mentioned specific embodiments are only illustrative, rather than restrictive. Under the inspiration, many modifications can be made without departing from the gist of the present invention, and these all belong to the protection of the present invention.
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| CN201410819869.9ACN104567728A (en) | 2014-12-24 | 2014-12-24 | Laser vision profile measurement system, measurement method and three-dimensional target |
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| CN201410819869.9ACN104567728A (en) | 2014-12-24 | 2014-12-24 | Laser vision profile measurement system, measurement method and three-dimensional target |
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|---|---|
| CN104567728Atrue CN104567728A (en) | 2015-04-29 |
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410819869.9APendingCN104567728A (en) | 2014-12-24 | 2014-12-24 | Laser vision profile measurement system, measurement method and three-dimensional target |
| Country | Link |
|---|---|
| CN (1) | CN104567728A (en) |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104897142A (en)* | 2015-06-11 | 2015-09-09 | 湖北工业大学 | Three-dimensional target for binocular or multi-view vision dimension measuring |
| CN105091866A (en)* | 2015-09-11 | 2015-11-25 | 天津大学 | Part position and posture identification visual system and calibration method thereof |
| CN105403230A (en)* | 2015-11-27 | 2016-03-16 | 财团法人车辆研究测试中心 | Object coordinate fusion correction method and correction plate device thereof |
| CN105509654A (en)* | 2015-12-31 | 2016-04-20 | 天津市东方龙光电测控技术有限公司 | Multi-angle mobile target structure |
| CN106600648A (en)* | 2016-12-06 | 2017-04-26 | 合肥工业大学 | Stereo coding target for calibrating internal parameter and distortion coefficient of camera and calibration method thereof |
| CN106840033A (en)* | 2017-03-13 | 2017-06-13 | 武汉理工大学 | A kind of profile of steel rail detection means and method based on image procossing |
| CN108120390A (en)* | 2016-11-30 | 2018-06-05 | 财团法人工业技术研究院 | Measuring apparatus and measuring method |
| CN108507466A (en)* | 2018-03-29 | 2018-09-07 | 大连理工大学 | The method that three-dimensional precise information is obtained using two-dimentional line laser scanner |
| CN108844459A (en)* | 2018-05-03 | 2018-11-20 | 华中科技大学无锡研究院 | A kind of scaling method and device of leaf digital template detection system |
| CN109341746A (en)* | 2018-12-10 | 2019-02-15 | 中国航空工业集团公司北京长城计量测试技术研究所 | A kind of three-dimensional standard of multisystem cooperative calibration |
| CN109521742A (en)* | 2018-12-05 | 2019-03-26 | 西安交通大学 | A kind of control system and control method for electric rotary body |
| CN109631764A (en)* | 2018-11-22 | 2019-04-16 | 南京理工大学 | Size Measuring System and method based on RealSense camera |
| CN109631770A (en)* | 2018-12-26 | 2019-04-16 | 深圳市合尔为科技有限公司 | The measuring device and measuring method of dimension of object |
| CN110411339A (en)* | 2019-07-30 | 2019-11-05 | 中国海洋大学 | An underwater target size measurement device and method based on parallel laser beams |
| CN110487213A (en)* | 2019-08-19 | 2019-11-22 | 杭州电子科技大学 | Full view line laser structured light three-dimensional image forming apparatus and method based on spatial offset |
| CN110764096A (en)* | 2019-09-24 | 2020-02-07 | 浙江华消科技有限公司 | Three-dimensional map construction method for disaster area, robot and robot control method |
| CN110953988A (en)* | 2019-12-04 | 2020-04-03 | 易思维（杭州）科技有限公司 | Three-dimensional block and method for evaluating accuracy of linear structure optical sensor by using same |
| CN111811463A (en)* | 2020-06-02 | 2020-10-23 | 中国海洋石油集团有限公司 | Method for accurately measuring span of stand column at bottom of block |
| CN112629435A (en)* | 2020-11-17 | 2021-04-09 | 重庆文理学院 | Gear measuring system and method based on multi-line structured light |
| CN113050428A (en)* | 2021-03-26 | 2021-06-29 | 清华大学 | Position pivot element contour tracking algorithm based on time-varying internal model |
| CN113175870A (en)* | 2021-04-23 | 2021-07-27 | 天津大学 | Global calibration target and calibration method for global calibration of multi-view vision sensor |
| CN115839675A (en)* | 2023-02-20 | 2023-03-24 | 宜科(天津)电子有限公司 | Object contour line recognition system |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5083073A (en)* | 1990-09-20 | 1992-01-21 | Mazada Motor Manufacturing U.S.A. Corp. | Method and apparatus for calibrating a vision guided robot |
| CN1455222A (en)* | 2003-04-11 | 2003-11-12 | 天津大学 | A camera calibration method and its implementing device |
| JP2004271292A (en)* | 2003-03-07 | 2004-09-30 | Meidensha Corp | Calibrator and stereo camera position/attitude calibration device |
| CN103411553A (en)* | 2013-08-13 | 2013-11-27 | 天津大学 | Fast calibration method of multiple line structured light visual sensor |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5083073A (en)* | 1990-09-20 | 1992-01-21 | Mazada Motor Manufacturing U.S.A. Corp. | Method and apparatus for calibrating a vision guided robot |
| JP2004271292A (en)* | 2003-03-07 | 2004-09-30 | Meidensha Corp | Calibrator and stereo camera position/attitude calibration device |
| CN1455222A (en)* | 2003-04-11 | 2003-11-12 | 天津大学 | A camera calibration method and its implementing device |
| CN103411553A (en)* | 2013-08-13 | 2013-11-27 | 天津大学 | Fast calibration method of multiple line structured light visual sensor |
| Title |
|---|
| 王中亚 等: "热轧圆钢截面轮廓及直径结构光在线检测系统", 《仪器仪表学报》* |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104897142A (en)* | 2015-06-11 | 2015-09-09 | 湖北工业大学 | Three-dimensional target for binocular or multi-view vision dimension measuring |
| CN105091866A (en)* | 2015-09-11 | 2015-11-25 | 天津大学 | Part position and posture identification visual system and calibration method thereof |
| CN105403230A (en)* | 2015-11-27 | 2016-03-16 | 财团法人车辆研究测试中心 | Object coordinate fusion correction method and correction plate device thereof |
| CN105403230B (en)* | 2015-11-27 | 2018-11-20 | 财团法人车辆研究测试中心 | Object coordinate fusion correction method and correction plate device |
| CN105509654A (en)* | 2015-12-31 | 2016-04-20 | 天津市东方龙光电测控技术有限公司 | Multi-angle mobile target structure |
| CN108120390A (en)* | 2016-11-30 | 2018-06-05 | 财团法人工业技术研究院 | Measuring apparatus and measuring method |
| US10495451B2 (en) | 2016-11-30 | 2019-12-03 | Industrial Technology Research Institute | Measuring equipment and measuring method |
| CN106600648A (en)* | 2016-12-06 | 2017-04-26 | 合肥工业大学 | Stereo coding target for calibrating internal parameter and distortion coefficient of camera and calibration method thereof |
| CN106840033A (en)* | 2017-03-13 | 2017-06-13 | 武汉理工大学 | A kind of profile of steel rail detection means and method based on image procossing |
| CN108507466B (en)* | 2018-03-29 | 2019-06-21 | 大连理工大学 | A method of obtaining accurate 3D data by using a 2D line laser scanner |
| CN108507466A (en)* | 2018-03-29 | 2018-09-07 | 大连理工大学 | The method that three-dimensional precise information is obtained using two-dimentional line laser scanner |
| CN108844459A (en)* | 2018-05-03 | 2018-11-20 | 华中科技大学无锡研究院 | A kind of scaling method and device of leaf digital template detection system |
| CN108844459B (en)* | 2018-05-03 | 2020-07-03 | 华中科技大学无锡研究院 | Calibration method and device of blade digital sample plate detection system |
| CN109631764A (en)* | 2018-11-22 | 2019-04-16 | 南京理工大学 | Size Measuring System and method based on RealSense camera |
| CN109631764B (en)* | 2018-11-22 | 2020-12-04 | 南京理工大学 | Dimensional measurement system and method based on RealSense camera |
| CN109521742A (en)* | 2018-12-05 | 2019-03-26 | 西安交通大学 | A kind of control system and control method for electric rotary body |
| CN109341746A (en)* | 2018-12-10 | 2019-02-15 | 中国航空工业集团公司北京长城计量测试技术研究所 | A kind of three-dimensional standard of multisystem cooperative calibration |
| CN109631770A (en)* | 2018-12-26 | 2019-04-16 | 深圳市合尔为科技有限公司 | The measuring device and measuring method of dimension of object |
| CN110411339A (en)* | 2019-07-30 | 2019-11-05 | 中国海洋大学 | An underwater target size measurement device and method based on parallel laser beams |
| CN110411339B (en)* | 2019-07-30 | 2021-07-02 | 中国海洋大学 | A kind of underwater target size measurement device and method based on parallel laser beam |
| CN110487213A (en)* | 2019-08-19 | 2019-11-22 | 杭州电子科技大学 | Full view line laser structured light three-dimensional image forming apparatus and method based on spatial offset |
| CN110487213B (en)* | 2019-08-19 | 2022-01-11 | 杭州电子科技大学 | A full-view line laser scanning 3D imaging device and method based on spatial dislocation |
| CN110764096A (en)* | 2019-09-24 | 2020-02-07 | 浙江华消科技有限公司 | Three-dimensional map construction method for disaster area, robot and robot control method |
| CN110953988A (en)* | 2019-12-04 | 2020-04-03 | 易思维（杭州）科技有限公司 | Three-dimensional block and method for evaluating accuracy of linear structure optical sensor by using same |
| CN111811463A (en)* | 2020-06-02 | 2020-10-23 | 中国海洋石油集团有限公司 | Method for accurately measuring span of stand column at bottom of block |
| CN111811463B (en)* | 2020-06-02 | 2022-07-01 | 中国海洋石油集团有限公司 | Method for accurately measuring span of stand column at bottom of block |
| CN112629435A (en)* | 2020-11-17 | 2021-04-09 | 重庆文理学院 | Gear measuring system and method based on multi-line structured light |
| CN112629435B (en)* | 2020-11-17 | 2023-11-07 | 重庆文理学院 | Gear measuring system and method based on multi-line structured light |
| CN113050428A (en)* | 2021-03-26 | 2021-06-29 | 清华大学 | Position pivot element contour tracking algorithm based on time-varying internal model |
| CN113050428B (en)* | 2021-03-26 | 2021-12-07 | 清华大学 | Position pivot element contour tracking algorithm based on time-varying internal model |
| CN113175870A (en)* | 2021-04-23 | 2021-07-27 | 天津大学 | Global calibration target and calibration method for global calibration of multi-view vision sensor |
| CN115839675A (en)* | 2023-02-20 | 2023-03-24 | 宜科(天津)电子有限公司 | Object contour line recognition system |
| Publication | Publication Date | Title |
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