单摄像机视觉测量网络系统关键技术的研究
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摘要
随着科学技术的迅猛发展，现代化生产对加工精度及装配精度的测量技术要求越来越高，尤其在航空、航天、军工及民用等领域，大部分情况下要求生产在现场进行实时监测及测量。近几年，三维测量技术得到深入地发展，广泛应用于工业检测、逆向工程、机器人视觉、虚拟现实等主动、实时测量过程。视觉测量技术的崛起，在一个全新的坐标测量思路上满足了现代化生产对高精度立体整体现场测量技术与设备的日益迫切的需求。
本文在分析和研究了目前的三维坐标视觉测量理论的基础上，提出一种基于光学特征点成像原理的单摄像机视觉测量网络系统的测量方法。即通过摄像机在多个测量网络控制点位置对预先建立的光学测棒上的光学特征点进行测量，进而得出在不同测量网络控制点位置的被测点的空间坐标。并将测量结果归一化到同一世界坐标系下，得到被测体的完整测量数据，实现整体测量。
为实现整体测量，本文首先搭建摄像机视觉测量网络系统，并阐述测量系统的工作原理。根据系统网络坐标系的建立及空间几何关系，建立测量系统模型。基于总体最小二乘算法，提出一种自适应总体最小二乘算法对光学特征点的姿态进行解算。根据预先定义的光学测棒的几何约束条件确定光学测头的空间坐标，进而求出被测点的空间坐标。
被测点的三维坐标通过视觉测量系统体现在光学特征点的二维图像平面坐标中，因此，三维坐标测量精度要受到光学特征点成像的亚像素定位精度的影响。本文在灰度平方加权质心定位算法的基础上，提出了双三次插值灰度平方加权质心定位算法，增加光学特征点成像中心周围有效像素点的个数，通过灰度平方加权减小噪声误差，改善特征点成像中心的定位精度，实现对光学特征点的精确定位。通过对比实验验证该方法的有效性。
视觉测量中被测量的三维空间点和对应的二维图像点之间的相互关系是由摄像机的成像几何模型决定的，三维空间点的坐标求解精度要受到摄像机参数的影响，为了提高视觉测量系统的整体测量精度，就必须对摄像机参数进行精确校准，从而将参数校准误差对整体视觉测量系统性能的影响程度降低到最小。本文对已有的摄像机参数校准方法进行了分析，在此基础上结合摄像机参数校准技术要求提出一种基于粒子群优化算法的摄像机内参数虚拟立体校准方法，通过摄像机内外参数建立摄像机成像模型，通过最小二乘线性算法对摄像机参数进行初始值估计，对基于粒子群优化算法的摄像机内参数优化校准方法进行了深入的研究和阐述，通过与其它校准方法的对比实验证明该方法具有较高的校准精度，能够满足大尺寸视觉测量系统对摄像机内参数精确校准的技术要求。
视觉测量网络系统在进行摄像机精确校准和质心定位之后，需要将多个网络控制点得到的测量数据归一到同一坐标系下，这里本文基于四元数法，将n个测量网络控制点位置的测量结果归一化，从而获得全局数据，实现整体测量。并通过加权数据融合优化算法将对单个被测点在多个网络控制点获得的测量数据融合。通过仿真对比实验验证该方法的有效性，证明视觉测量网络系统的建立能够扩大测量范围和提高测量精度。
通过测量系统的总体测试，对仿真结果的计算进行评估，确定测量系统的最优方案。并且，对测试结果的不确定度及标准偏差进行评估，验证了摄像机视觉测量网络系统的有效性和准确性。
With the rapid development of scientific technology, the requirement ofmodern production on machining precision and assembly precision measurementtechnology is more and more high, especially in the fields of aerospace militaryand civil, in most cases, requires production in the field real-time monitoring andmeasurement. In recent years, the three dimensional measurement technology hasget further development, widely applied in industrial detection, reverseengineering, robot visual, virtual reality, as well as other active real-timemeasuring process. The rising of visual measurement technology is just a newcoordinate measuring way to satisfy the urgent increasingly demand of themodern production of high-precision stereo whole field measurement technologyand equipment.
Based on the analysis and research on the current3D coordinate visionmeasuring theory, the paper presents a kind of method on single camera visionmeasurement based on optical imaging principle of characteristic points. So thecamera measures the optical characteristic point on the beforehand opticalmeasuring rod in the position of multi network control points, then get the spacecoordinates of the measuring point in the position of the different networkcontrol points. And the measurement results are taken the normalization into thesame world coordinate system, then get the completed measurement result,achieve the global measurement.
In order to achieve the global measurement, the paper sets up the singlecamera visual measurement network system in the first, and expounds the workprinciple of the measurement system. According to the building of the networkcoordinate system and the space geometry relationship, sets up the model ofmeasurement network system. Based on the total least squares algorithm, the paper presents the adaptive total least squares optimization algorithm to calculatethe attitude of optical characteristic point, defines the space coordinates ofoptical measurement probe according to the geometric constraint of thepre-defined optical measurement rod, then finds out the space coordinates ofmeasured point.
The3D coordinates of measured point is embodied in the2D imaging planecoordinates of the optical characteristics point through the visual measuringsystem, therefore, the measurement precision of3D coordinates is affected by thesubpixel location precision of optical characteristics point's imaging. Based onthe gray square weighted centroid localization algorithm, the paper presents thedouble cubic interpolation-gray square weighted centroid localization algorithm,increases the number of effective pixels around the optical characteristic pointimaging center, and reduces noise error through the gray square weighted,improves the imaging center positioning accuracy of optical characteristics point,realizes the accurate positioning of the optical characteristic points, And verifiesthe effectiveness of the method via comparing the experimental results.
In the visual measurement, the relationship between the measured threedimensional space point and the corresponding two dimensional image point isdecided by the camera imaging geometrical model, the measurement precision ofthree dimensional space point coordinates is affected by camera parameters. Inorder to improve the overall measurement accuracy of visual measurment system,it must make the camera parameters calibrate accurately, so that the influencedegree of the parameter calibration error to the whole visual measuring systemperformance could be reduced to minimum. In the paper, the existing cameraparameter calibration methods are analyzed based on this camera parametercalibration technical requirements. It proposes a kind of virtual stereo cameraintrinsic parameters calibration methods based on particle swarm optimizationalgorithm, establishes camera imaging model through the camera internal andexternal parameters, initial value of the linear camera parameters is estimated viathe least squares algorithm, further researches and expounds the camera intrinsicparameters optimization calibration method based on particle swarm optimization algorithm. Compared with other calibration methods, it can provethat the method has higher accuracy in calibration, and satisfies the technicalrequirements of camera intrinsic parameters accurate calibration for the large sizevisual measurement system.
After accurately calibrated and centroid localized, the visual measurementnetwork system need make the measuring data of much more network controlpoints taken the normalizaiton into the same coordinate system, the paper usesthe quaternion algorithm to take the normalizaiton for the measurement results inthe position of n measurement network control points, so as to achieve globaldata, and realize the whole measure. And the measurement results of singlemeasured point in the postion of multi network control points will be fused viathe weighted data fusion optimization algorithm. The simulation experimentsverify the validity of this method and prove that the establishment of the visualmeasurement network system can expand the range of measurement and improvethe accuracy of measurement.
Evaluating the simulation results of calculation through the wholemeasurement of the measurement system, then defining the optimal scheme ofthe measurement system, Same time, evaluating the uncertainty evaluation andstandard deviation of the measurement results, it verifies the effectiveness andaccuracy of the single camera visual measurement network system.
本文在分析和研究了目前的三维坐标视觉测量理论的基础上，提出一种基于光学特征点成像原理的单摄像机视觉测量网络系统的测量方法。即通过摄像机在多个测量网络控制点位置对预先建立的光学测棒上的光学特征点进行测量，进而得出在不同测量网络控制点位置的被测点的空间坐标。并将测量结果归一化到同一世界坐标系下，得到被测体的完整测量数据，实现整体测量。
为实现整体测量，本文首先搭建摄像机视觉测量网络系统，并阐述测量系统的工作原理。根据系统网络坐标系的建立及空间几何关系，建立测量系统模型。基于总体最小二乘算法，提出一种自适应总体最小二乘算法对光学特征点的姿态进行解算。根据预先定义的光学测棒的几何约束条件确定光学测头的空间坐标，进而求出被测点的空间坐标。
被测点的三维坐标通过视觉测量系统体现在光学特征点的二维图像平面坐标中，因此，三维坐标测量精度要受到光学特征点成像的亚像素定位精度的影响。本文在灰度平方加权质心定位算法的基础上，提出了双三次插值灰度平方加权质心定位算法，增加光学特征点成像中心周围有效像素点的个数，通过灰度平方加权减小噪声误差，改善特征点成像中心的定位精度，实现对光学特征点的精确定位。通过对比实验验证该方法的有效性。
视觉测量中被测量的三维空间点和对应的二维图像点之间的相互关系是由摄像机的成像几何模型决定的，三维空间点的坐标求解精度要受到摄像机参数的影响，为了提高视觉测量系统的整体测量精度，就必须对摄像机参数进行精确校准，从而将参数校准误差对整体视觉测量系统性能的影响程度降低到最小。本文对已有的摄像机参数校准方法进行了分析，在此基础上结合摄像机参数校准技术要求提出一种基于粒子群优化算法的摄像机内参数虚拟立体校准方法，通过摄像机内外参数建立摄像机成像模型，通过最小二乘线性算法对摄像机参数进行初始值估计，对基于粒子群优化算法的摄像机内参数优化校准方法进行了深入的研究和阐述，通过与其它校准方法的对比实验证明该方法具有较高的校准精度，能够满足大尺寸视觉测量系统对摄像机内参数精确校准的技术要求。
视觉测量网络系统在进行摄像机精确校准和质心定位之后，需要将多个网络控制点得到的测量数据归一到同一坐标系下，这里本文基于四元数法，将n个测量网络控制点位置的测量结果归一化，从而获得全局数据，实现整体测量。并通过加权数据融合优化算法将对单个被测点在多个网络控制点获得的测量数据融合。通过仿真对比实验验证该方法的有效性，证明视觉测量网络系统的建立能够扩大测量范围和提高测量精度。
通过测量系统的总体测试，对仿真结果的计算进行评估，确定测量系统的最优方案。并且，对测试结果的不确定度及标准偏差进行评估，验证了摄像机视觉测量网络系统的有效性和准确性。
With the rapid development of scientific technology, the requirement ofmodern production on machining precision and assembly precision measurementtechnology is more and more high, especially in the fields of aerospace militaryand civil, in most cases, requires production in the field real-time monitoring andmeasurement. In recent years, the three dimensional measurement technology hasget further development, widely applied in industrial detection, reverseengineering, robot visual, virtual reality, as well as other active real-timemeasuring process. The rising of visual measurement technology is just a newcoordinate measuring way to satisfy the urgent increasingly demand of themodern production of high-precision stereo whole field measurement technologyand equipment.
Based on the analysis and research on the current3D coordinate visionmeasuring theory, the paper presents a kind of method on single camera visionmeasurement based on optical imaging principle of characteristic points. So thecamera measures the optical characteristic point on the beforehand opticalmeasuring rod in the position of multi network control points, then get the spacecoordinates of the measuring point in the position of the different networkcontrol points. And the measurement results are taken the normalization into thesame world coordinate system, then get the completed measurement result,achieve the global measurement.
In order to achieve the global measurement, the paper sets up the singlecamera visual measurement network system in the first, and expounds the workprinciple of the measurement system. According to the building of the networkcoordinate system and the space geometry relationship, sets up the model ofmeasurement network system. Based on the total least squares algorithm, the paper presents the adaptive total least squares optimization algorithm to calculatethe attitude of optical characteristic point, defines the space coordinates ofoptical measurement probe according to the geometric constraint of thepre-defined optical measurement rod, then finds out the space coordinates ofmeasured point.
The3D coordinates of measured point is embodied in the2D imaging planecoordinates of the optical characteristics point through the visual measuringsystem, therefore, the measurement precision of3D coordinates is affected by thesubpixel location precision of optical characteristics point's imaging. Based onthe gray square weighted centroid localization algorithm, the paper presents thedouble cubic interpolation-gray square weighted centroid localization algorithm,increases the number of effective pixels around the optical characteristic pointimaging center, and reduces noise error through the gray square weighted,improves the imaging center positioning accuracy of optical characteristics point,realizes the accurate positioning of the optical characteristic points, And verifiesthe effectiveness of the method via comparing the experimental results.
In the visual measurement, the relationship between the measured threedimensional space point and the corresponding two dimensional image point isdecided by the camera imaging geometrical model, the measurement precision ofthree dimensional space point coordinates is affected by camera parameters. Inorder to improve the overall measurement accuracy of visual measurment system,it must make the camera parameters calibrate accurately, so that the influencedegree of the parameter calibration error to the whole visual measuring systemperformance could be reduced to minimum. In the paper, the existing cameraparameter calibration methods are analyzed based on this camera parametercalibration technical requirements. It proposes a kind of virtual stereo cameraintrinsic parameters calibration methods based on particle swarm optimizationalgorithm, establishes camera imaging model through the camera internal andexternal parameters, initial value of the linear camera parameters is estimated viathe least squares algorithm, further researches and expounds the camera intrinsicparameters optimization calibration method based on particle swarm optimization algorithm. Compared with other calibration methods, it can provethat the method has higher accuracy in calibration, and satisfies the technicalrequirements of camera intrinsic parameters accurate calibration for the large sizevisual measurement system.
After accurately calibrated and centroid localized, the visual measurementnetwork system need make the measuring data of much more network controlpoints taken the normalizaiton into the same coordinate system, the paper usesthe quaternion algorithm to take the normalizaiton for the measurement results inthe position of n measurement network control points, so as to achieve globaldata, and realize the whole measure. And the measurement results of singlemeasured point in the postion of multi network control points will be fused viathe weighted data fusion optimization algorithm. The simulation experimentsverify the validity of this method and prove that the establishment of the visualmeasurement network system can expand the range of measurement and improvethe accuracy of measurement.
Evaluating the simulation results of calculation through the wholemeasurement of the measurement system, then defining the optimal scheme ofthe measurement system, Same time, evaluating the uncertainty evaluation andstandard deviation of the measurement results, it verifies the effectiveness andaccuracy of the single camera visual measurement network system.
引文
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