光笔式便携三坐标测量系统测头标定及相关技术研究
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摘要
光笔式三坐标测量系统基于视觉测量技术,具有重量轻、便携性好、组建灵活、操作简单、精度适中、测量不受被测物体表面差异影响等优点,代表着坐标测量技术的一个重要发展方向,具有广阔的应用背景。本课题组于2000年开始这项研究,取得了一系列成果。由于现场测量往往需要对光笔测头进行标定,围绕光笔测头的标定及相关技术,本论文做了如下工作:
1、介绍了当前便携式三维坐标测量技术特别是其中的手持探头式便携坐标测量技术;
2、从PNP问题的解的角度说明了光笔设计的正确性;
3、通过对图像中测量背景对光笔控制点识别和处理造成干扰的部分进行屏蔽,使得在复杂背景下提取光笔区域成为可能,提高了控制点边缘和中心的定位精度;
4、创造性地提出采用两种模式进行控制点中心定位。一种是经Canny边缘检测获得控制点边缘后,对边缘进行最小二乘椭圆拟合,用椭圆中心近似控制点中心,适用于近距离测量;另一种是对控制点中心初步定位后用改进的高斯曲面拟合法获得亚像素级的曲面极值点,适用于较远距离的测量。并给出了两种模式的控制点中心定位重复性精度。
5、建立了测头中心在光笔坐标系中的坐标值的估算模型。利用一个标准锥,即可实现光笔测头的现场标定。实验证明利用标定所得测头数据进行测量,亦可达到使用测头中心精密位置数据时的测量精度。
6、光笔式便携三坐标测量系统的测量精度与Brown-Sharp精密三坐标测量机的精度比对实验证明了前者测量的正确性。1.5m距离测量和4m距离测量的误差都在可容许的范围内。分析了系统的误差来源,提出了两种系统改进方案,一种是利用透视投影变换的直线不变性修正控制点中心在像面上的坐标,另一种是利用可控恒流源对控制点亮度进行调整。
The light pen portable coordinate measuring system based on photogrammetry technology possesses many advantages such as light and portable device, fast and flexible construction, simple operation, precision of proper level, not been affected by differences of surfaces been measured. So it is an important representation of one of the directions of the development of the coordinate measuring technology. It has wide prospective applications in many fields. Our team began the research of this system in 2000 and has acquired a lot since that time. In order to realize the probe tip calibration for the light pen portable coordinate measuring system to assist the field measurement, the following work was done.
1. Various portable 3D coordinate measuring systems, especially the hand-hold probe 3D coordinate measuring system, are introduced.
2. The validity of the design of the light pen is explained from the perspective of the PNP problem.
3. Eradicating the districts which can disturb the recognition of the control points of the light pen to obtain the very image district of the light pen. This can lend help to the edge detection of the image of the control points, thus can make the edge detected more precise.
4. Two modes employed for the location of the center of the control points are introduced. One is to first obtain the edge of the control points, then use the least square ellipse fitting method to get the center of the control points. The other is to first obtain the initial center of the control points, and then the improved Gauss surface fitting method is employed. The maximum of the Gauss surfaces are considered to be the centers of the control points. The former is proper for the measurement of nearer objects, whereas the latter is proper for the measurement of further objects. The repeatability error of the two modes is given.
5. The mathematical model for the coordinates of the probe tip center under the light pen coordinate system has been built. Simply with a standard cone, the probe tip center can be calibrated. Experiment showed that the measuring precision of the light pen portable coordinate measuring system could reach to the same level as with the measured probe tip center data when with the calculated probe tip center data.
6. The measuring precision of the light pen portable coordinate measuring system have been compared with the Brown-Sharp coordinate measuring machine. This comparison proved the correctness of the mathematical model of the light pen portable coordinate measuring system. Experiment showed that the measuring errors of the light pen portable coordinate measuring system in distances of 1.5m and 4m are both tolerable. The sources of the measuring error have been discussed. Two methods to further improve the system are presented. One is to enable self-rectification of the light pen using the principle of projective invariance of lines. The other is to make the luminance of the LEDs be controlled by adjustable current source.
1、介绍了当前便携式三维坐标测量技术特别是其中的手持探头式便携坐标测量技术;
2、从PNP问题的解的角度说明了光笔设计的正确性;
3、通过对图像中测量背景对光笔控制点识别和处理造成干扰的部分进行屏蔽,使得在复杂背景下提取光笔区域成为可能,提高了控制点边缘和中心的定位精度;
4、创造性地提出采用两种模式进行控制点中心定位。一种是经Canny边缘检测获得控制点边缘后,对边缘进行最小二乘椭圆拟合,用椭圆中心近似控制点中心,适用于近距离测量;另一种是对控制点中心初步定位后用改进的高斯曲面拟合法获得亚像素级的曲面极值点,适用于较远距离的测量。并给出了两种模式的控制点中心定位重复性精度。
5、建立了测头中心在光笔坐标系中的坐标值的估算模型。利用一个标准锥,即可实现光笔测头的现场标定。实验证明利用标定所得测头数据进行测量,亦可达到使用测头中心精密位置数据时的测量精度。
6、光笔式便携三坐标测量系统的测量精度与Brown-Sharp精密三坐标测量机的精度比对实验证明了前者测量的正确性。1.5m距离测量和4m距离测量的误差都在可容许的范围内。分析了系统的误差来源,提出了两种系统改进方案,一种是利用透视投影变换的直线不变性修正控制点中心在像面上的坐标,另一种是利用可控恒流源对控制点亮度进行调整。
The light pen portable coordinate measuring system based on photogrammetry technology possesses many advantages such as light and portable device, fast and flexible construction, simple operation, precision of proper level, not been affected by differences of surfaces been measured. So it is an important representation of one of the directions of the development of the coordinate measuring technology. It has wide prospective applications in many fields. Our team began the research of this system in 2000 and has acquired a lot since that time. In order to realize the probe tip calibration for the light pen portable coordinate measuring system to assist the field measurement, the following work was done.
1. Various portable 3D coordinate measuring systems, especially the hand-hold probe 3D coordinate measuring system, are introduced.
2. The validity of the design of the light pen is explained from the perspective of the PNP problem.
3. Eradicating the districts which can disturb the recognition of the control points of the light pen to obtain the very image district of the light pen. This can lend help to the edge detection of the image of the control points, thus can make the edge detected more precise.
4. Two modes employed for the location of the center of the control points are introduced. One is to first obtain the edge of the control points, then use the least square ellipse fitting method to get the center of the control points. The other is to first obtain the initial center of the control points, and then the improved Gauss surface fitting method is employed. The maximum of the Gauss surfaces are considered to be the centers of the control points. The former is proper for the measurement of nearer objects, whereas the latter is proper for the measurement of further objects. The repeatability error of the two modes is given.
5. The mathematical model for the coordinates of the probe tip center under the light pen coordinate system has been built. Simply with a standard cone, the probe tip center can be calibrated. Experiment showed that the measuring precision of the light pen portable coordinate measuring system could reach to the same level as with the measured probe tip center data when with the calculated probe tip center data.
6. The measuring precision of the light pen portable coordinate measuring system have been compared with the Brown-Sharp coordinate measuring machine. This comparison proved the correctness of the mathematical model of the light pen portable coordinate measuring system. Experiment showed that the measuring errors of the light pen portable coordinate measuring system in distances of 1.5m and 4m are both tolerable. The sources of the measuring error have been discussed. Two methods to further improve the system are presented. One is to enable self-rectification of the light pen using the principle of projective invariance of lines. The other is to make the luminance of the LEDs be controlled by adjustable current source.
引文
[1]彭凯,基于光靶标的双相机三坐标测量系统关键技术的研究:[博士学位论文],天津:天津大学,2007
[2]张国雄,三坐标测量机,天津:天津大学出版社,1999:1~17
[3]彭凯,光笔三坐标视觉测量系统关键技术的研究:[硕士学位论文],天津:天津大学,2004
[4]郭辉,关节臂式柔性三坐标测量系统关键技术的研究:[硕士学位论文],天津:天津大学,2005
[5] Accurex公司产品介绍,Internet资料,www.accurexmeasurement.com
[6]廖强,周忆,米林等,机器视觉在精密测量中的应用,重庆大学学报,2002,25(6):1~4
[7]吴子彦,大视场双目视觉传感器标定方法研究:[硕士学位论文],北京:北京航空航天大学,2008
[8] FishlerM A, Bolles R C, Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM, 1981, 24(6):381~395
[9]胡占义,雷成,吴福朝,关于P4P问题的一点讨论,自动化学报,2001,27(6):770~776
[10] Haralick RM, Lee C-N, Ottenberg K, etc, Analysis and solution of the three point perspective pose estimation problem, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Hawaii, 1991: 592~598
[11] Wolfe WJ, Mathis D, The perspective view of three points, IEEE Transactions on Pattern Analysis and machine Intelligence, 1991,13(1):66~73
[12] Yuan J S–C,A general photogrammetric method for determining object position and orientation,IEEE Trans on Robotics and Automation, 1989, 5(2):129~142
[13]张广军,机器视觉,科学出版社, 2005
[14] Zhang Z, A flexible new technique for camera calibration, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(11):1330~1334
[15] Song LM,Wang MP,Lu L, et al, High precision camera calibration in vision measurement, Optics&Laser Technology, 2007, 39(7): 1413~1420
[16]章毓晋,图像工程中册,北京:清华大学出版社,2005
[17]徐殿武,位图文件操作的程序设计的研究,微计算机信息,2007,24(5-3):176~178
[18]肖蕾,何坤,周激流等,改进自适应中值滤波的图像去噪,激光杂志,2009,30(2):44~46
[19]张旭光,张玉起,杨洪波,浅谈图像预处理对轮廓提取的影响,今日科苑,2007,(18):172
[20]周心明,兰赛,徐燕,图像处理中几种边缘检测算法的比较,现代电力,2000,17(3):65~69
[21]徐献灵,林奕水,图像边缘检测算法比较与分析,自动化与信息工程,2007,28(3):44~46
[22] V Torre, T Poggio, On edge detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(2): 147~163
[23] Djemel Ziou, Salvatore Tabbone, Edge Detection Techniques-An Overview, Pattern Recognition & Image Analysis, 1998, 8(4): 537~559
[24]陈荣盛,袁小海,水下机器人目标搜索与识别算法,中国海洋平台,1999,14(4):37~42
[25]王爱民,赵忠旭,基于矢量Prewitt算子的多尺度彩色图象边缘检测方法,中国图象图形学报,1999,12(4):1024~1028
[26] Lilian Ji, Hong Yan, Attractable snakes based on the greedy algorithm for contour extraction, Pattern Recognition, 2002, 35(4): 791~806
[27] John Canny, A Computational Approach to Edge Detection[C], IEEE Trans, 1986, PAMI, 8:679~698
[28] Zhang Bin, He Saixian, Improved Edge detection Method Based on Canny algorithm, Infrared Technology, 2006, 28 (3):165~169
[29]梁光明,孙即祥,马琦,姚春光,Otsu算法在Canny算子中的应用,国防科技大学学报,2003,25(5):36~39
[30] Andrew W. Fitzgibbon, Maurizio Pilu, Robert B. Fisher, Direct Least Squares Fitting of Ellipses, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1999, 21(5): 476~480
[31]刘书桂,李蓬,那永林,基于最小二乘原理的平面任意位置椭圆的评价,计量学报,2002,23(4):245~247
[32]王冰,职秦川,张仲选,灰度图像质心快速算法,计算机辅助设计与图形学学报,2004,16(10):1360~1365
[33]铁菊红,彭辉,一种改进的基于高斯分布拟合的提取标志点像素坐标方法,计算机与现代化,2008,(4),58~60
[34]徐正伟,吴成柯,基于透视投影不变性的空间平面多边形识别,电子学报,1993(7):8~15
[35]雷尼绍测针测头产品选购手册,Internet资料,www.taixi.com.cn
[36]周富强,张广军,江洁,空间圆几何参数的非接触高精度测量方法,仪器仪表学报,2004,25(5):604~607
[37]魏振忠,张广军,视觉检测中椭圆中心成像畸变误差模型研究,北京航空航天大学学报,2003,29(2),140~143
[38] Wallace AM, Industrial application of computer vision since1982, IEEE Proceedings, 1988: 117～136
[39]张靖,朱大勇,贾晓东,用共线点列标定摄像机镜头畸变,激光技术,2006,30(2):221~224
[40]贺俊吉,张广军,杨宪铭,基于交比不变性的镜头畸变参数标定方法,仪器仪表学报,2004,25(5):597~599
[41]郭阳,徐心和,交比不变量在机器视觉中的误差分析及应用,东北大学学报,2007,28(8):1077~1080
[42] Olivier Faugeras, Stratification of three dimensional vision: projective, affine, and metric representations, Optical Society of America, 1995, 12 (3):465~484
[43] Penna MA, Determining camera parameters from the perspective projection of a quadrilateral, Pattern Recognition, 1991, 24(6):533~541
[44] Abdel-Aziz Y, Karara H, Direct linear transformation from comparator to object space coordinates in close-range photogrammetry, ASP Symp, Close-Range Photogrammetry, Urbana, Illinois, 1971:1~18
[45]刘长英,车仁生,黄庆成等,视觉测量中光学特征点亮度控制方法研究,光学精密工程,2004,12(3):93~96
[2]张国雄,三坐标测量机,天津:天津大学出版社,1999:1~17
[3]彭凯,光笔三坐标视觉测量系统关键技术的研究:[硕士学位论文],天津:天津大学,2004
[4]郭辉,关节臂式柔性三坐标测量系统关键技术的研究:[硕士学位论文],天津:天津大学,2005
[5] Accurex公司产品介绍,Internet资料,www.accurexmeasurement.com
[6]廖强,周忆,米林等,机器视觉在精密测量中的应用,重庆大学学报,2002,25(6):1~4
[7]吴子彦,大视场双目视觉传感器标定方法研究:[硕士学位论文],北京:北京航空航天大学,2008
[8] FishlerM A, Bolles R C, Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM, 1981, 24(6):381~395
[9]胡占义,雷成,吴福朝,关于P4P问题的一点讨论,自动化学报,2001,27(6):770~776
[10] Haralick RM, Lee C-N, Ottenberg K, etc, Analysis and solution of the three point perspective pose estimation problem, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Hawaii, 1991: 592~598
[11] Wolfe WJ, Mathis D, The perspective view of three points, IEEE Transactions on Pattern Analysis and machine Intelligence, 1991,13(1):66~73
[12] Yuan J S–C,A general photogrammetric method for determining object position and orientation,IEEE Trans on Robotics and Automation, 1989, 5(2):129~142
[13]张广军,机器视觉,科学出版社, 2005
[14] Zhang Z, A flexible new technique for camera calibration, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(11):1330~1334
[15] Song LM,Wang MP,Lu L, et al, High precision camera calibration in vision measurement, Optics&Laser Technology, 2007, 39(7): 1413~1420
[16]章毓晋,图像工程中册,北京:清华大学出版社,2005
[17]徐殿武,位图文件操作的程序设计的研究,微计算机信息,2007,24(5-3):176~178
[18]肖蕾,何坤,周激流等,改进自适应中值滤波的图像去噪,激光杂志,2009,30(2):44~46
[19]张旭光,张玉起,杨洪波,浅谈图像预处理对轮廓提取的影响,今日科苑,2007,(18):172
[20]周心明,兰赛,徐燕,图像处理中几种边缘检测算法的比较,现代电力,2000,17(3):65~69
[21]徐献灵,林奕水,图像边缘检测算法比较与分析,自动化与信息工程,2007,28(3):44~46
[22] V Torre, T Poggio, On edge detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(2): 147~163
[23] Djemel Ziou, Salvatore Tabbone, Edge Detection Techniques-An Overview, Pattern Recognition & Image Analysis, 1998, 8(4): 537~559
[24]陈荣盛,袁小海,水下机器人目标搜索与识别算法,中国海洋平台,1999,14(4):37~42
[25]王爱民,赵忠旭,基于矢量Prewitt算子的多尺度彩色图象边缘检测方法,中国图象图形学报,1999,12(4):1024~1028
[26] Lilian Ji, Hong Yan, Attractable snakes based on the greedy algorithm for contour extraction, Pattern Recognition, 2002, 35(4): 791~806
[27] John Canny, A Computational Approach to Edge Detection[C], IEEE Trans, 1986, PAMI, 8:679~698
[28] Zhang Bin, He Saixian, Improved Edge detection Method Based on Canny algorithm, Infrared Technology, 2006, 28 (3):165~169
[29]梁光明,孙即祥,马琦,姚春光,Otsu算法在Canny算子中的应用,国防科技大学学报,2003,25(5):36~39
[30] Andrew W. Fitzgibbon, Maurizio Pilu, Robert B. Fisher, Direct Least Squares Fitting of Ellipses, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1999, 21(5): 476~480
[31]刘书桂,李蓬,那永林,基于最小二乘原理的平面任意位置椭圆的评价,计量学报,2002,23(4):245~247
[32]王冰,职秦川,张仲选,灰度图像质心快速算法,计算机辅助设计与图形学学报,2004,16(10):1360~1365
[33]铁菊红,彭辉,一种改进的基于高斯分布拟合的提取标志点像素坐标方法,计算机与现代化,2008,(4),58~60
[34]徐正伟,吴成柯,基于透视投影不变性的空间平面多边形识别,电子学报,1993(7):8~15
[35]雷尼绍测针测头产品选购手册,Internet资料,www.taixi.com.cn
[36]周富强,张广军,江洁,空间圆几何参数的非接触高精度测量方法,仪器仪表学报,2004,25(5):604~607
[37]魏振忠,张广军,视觉检测中椭圆中心成像畸变误差模型研究,北京航空航天大学学报,2003,29(2),140~143
[38] Wallace AM, Industrial application of computer vision since1982, IEEE Proceedings, 1988: 117～136
[39]张靖,朱大勇,贾晓东,用共线点列标定摄像机镜头畸变,激光技术,2006,30(2):221~224
[40]贺俊吉,张广军,杨宪铭,基于交比不变性的镜头畸变参数标定方法,仪器仪表学报,2004,25(5):597~599
[41]郭阳,徐心和,交比不变量在机器视觉中的误差分析及应用,东北大学学报,2007,28(8):1077~1080
[42] Olivier Faugeras, Stratification of three dimensional vision: projective, affine, and metric representations, Optical Society of America, 1995, 12 (3):465~484
[43] Penna MA, Determining camera parameters from the perspective projection of a quadrilateral, Pattern Recognition, 1991, 24(6):533~541
[44] Abdel-Aziz Y, Karara H, Direct linear transformation from comparator to object space coordinates in close-range photogrammetry, ASP Symp, Close-Range Photogrammetry, Urbana, Illinois, 1971:1~18
[45]刘长英,车仁生,黄庆成等,视觉测量中光学特征点亮度控制方法研究,光学精密工程,2004,12(3):93~96