基于光栅投影的牙颌三维测量系统研究
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摘要
随着人民物质生活水平的不断提高和人口老龄化发展,需进行口腔修复的人群数量不断增长。传统的修复体制造技术设计制作周期长,人工干预多,修复体质量难以保证,已无法满足临床需要。建立牙颌的三维数字化模型是实现牙颌修复体数字化设计加工的前提,是口腔CAD/CAM技术的重要组成部分,修复体的设计加工精度很大程度上取决于牙颌的测量精度。为此,本文研究了基于光栅投影的牙颌三维测量系统,主要研究内容如下:
本文描述了系统所选用的光栅投影法的测量原理以及测量思路,并基于模块化思路给出了测量系统的整体架构设计,具体包括牙颌定位模块、光路调整模块、视觉测量模块、产品外观模块、系统标定模块、编码解码模块、三维重构模块、点云拼合模块等八个模块;针对测量系统需求给出了详细的硬件选型和模块设计,为牙颌测量系统功能实现提供了基本保证。
本文研究了摄像机和投影仪标定方法,比较了各种标定方法的优劣,在此基础上针对广泛应用的张正友标定法,结合测量对象和系统进行了应用研究,为系统的整体精度提供了重要支撑。建立了无几何约束的三维重建模型,降低了对测量设备在加工装配方面的精度要求,有助于提升系统的稳定性。
本文针对牙颌的非接触式光学三维测量,提出了融入标定功能的夹具设计方法,实现了测量过程中待测物与标定靶的空间一致性;定义了单目视觉测量过程涉及到的坐标系统,提出了一种基于坐标配准的点云拼合技术,简化了点云拼合流程,实现了点云拼合理论零误差;通过实验验证,得到了具有一定精度的牙颌模型三维点云拼合数据,为提高牙颌测量系统的测量速度和整体精度提供了有力支撑。
利用本文的三维测量装置对牙颌模型进行了快速测量,实验测量过程稳定,单次测量不超1分钟,同时,取得了一定的精度。测量速度较快,取得了一定的精度,为口腔CAD/CAM修复技术获得原始点云提供了测量平台。同时,本文的研究成果可扩展应用到精密检测、文物复原等具有复杂曲面特征的小型待测物的数字化测量中。
With the continues improvement of people's living standards and the development of population aging in China, the population of people who needs mouth rehabilitation grows constantly. However, the design and manufacture cycle of the technology of traditional restoration manufacturing is long and difficult to guarantee the quality of restoration with more manual intervention,it has been unable to meet clinical needs. As an important part of the CAD / CAM technology on Prosthodontics, creating three-dimensional digital tooth jaw model is the precondition of achieving the digital design and manufacture of tooth jaw restorations. The precision of restoration depends largely on the measurement accuracy of tooth jaw. Therefore, in this paper the three dimensional measurement system of tooth jaw based on grating projection is studied and main contents are as follows.
This paper describes the measurement principle and the approach used in the system and proposes the overall framework of the measurement system based on the idea of modular, which includes the tooth jaw positioning module, optical path adjustment module, the visual measurement module, product appearance modules, system calibration module, encoding and decoding modules, three-dimensional reconstruction of the module and point cloud merging module. Meanwhile, this paper gives some details on the selection of the instruments used in the measurement system and the design of the listed modules above, which provides the basic guarantee for the measurement system to achieve the function.
This paper studies calibration methods of camera and projector and compares the pros and cons of various calibration methods. On the basis of Zhang-Zhengyou calibration method widely used, the calibration method combined measurement objects and system characters is studied for application,which provides an important support for the overall accuracy of the system. It establishes a three-dimensional reconstruction model of non-geometric constraint, which makes a significant reduction of the demand of the precision of the system in the processing and assembly while the system may be relatively more stable.
In view of non-contact optical three dimensional measurement of tooth jaw, A jig design method which integrates the calibration function is proposed for realizing spatial coincidence during the process of objects to be measured and calibration target. The coordinate systems are defined monocular vision measurement process involved. A coordinate matching-based point clouds registration technology is proposed for simplifying the process of point clouds registration and simultaneously realizing the zero error of point clouds registration theory. With the experimental verification, cloud registration data with some precision is obtained, which significantly support the overall accuracy of dental measurement system.
The three dimensional measurement device in this article is used for tooth jaw measurement, the experimental process is stable, the period of single measurement is not more than 1 minute and a certain accuracy is achieved, which provides a digital measurement platform for CAD / CAM technology to access to the original point cloud. Meanwhile, the research in this article can be used for other objects to be measured with complex surface features, such as precision Measurement, Heritage, etc.
本文描述了系统所选用的光栅投影法的测量原理以及测量思路,并基于模块化思路给出了测量系统的整体架构设计,具体包括牙颌定位模块、光路调整模块、视觉测量模块、产品外观模块、系统标定模块、编码解码模块、三维重构模块、点云拼合模块等八个模块;针对测量系统需求给出了详细的硬件选型和模块设计,为牙颌测量系统功能实现提供了基本保证。
本文研究了摄像机和投影仪标定方法,比较了各种标定方法的优劣,在此基础上针对广泛应用的张正友标定法,结合测量对象和系统进行了应用研究,为系统的整体精度提供了重要支撑。建立了无几何约束的三维重建模型,降低了对测量设备在加工装配方面的精度要求,有助于提升系统的稳定性。
本文针对牙颌的非接触式光学三维测量,提出了融入标定功能的夹具设计方法,实现了测量过程中待测物与标定靶的空间一致性;定义了单目视觉测量过程涉及到的坐标系统,提出了一种基于坐标配准的点云拼合技术,简化了点云拼合流程,实现了点云拼合理论零误差;通过实验验证,得到了具有一定精度的牙颌模型三维点云拼合数据,为提高牙颌测量系统的测量速度和整体精度提供了有力支撑。
利用本文的三维测量装置对牙颌模型进行了快速测量,实验测量过程稳定,单次测量不超1分钟,同时,取得了一定的精度。测量速度较快,取得了一定的精度,为口腔CAD/CAM修复技术获得原始点云提供了测量平台。同时,本文的研究成果可扩展应用到精密检测、文物复原等具有复杂曲面特征的小型待测物的数字化测量中。
With the continues improvement of people's living standards and the development of population aging in China, the population of people who needs mouth rehabilitation grows constantly. However, the design and manufacture cycle of the technology of traditional restoration manufacturing is long and difficult to guarantee the quality of restoration with more manual intervention,it has been unable to meet clinical needs. As an important part of the CAD / CAM technology on Prosthodontics, creating three-dimensional digital tooth jaw model is the precondition of achieving the digital design and manufacture of tooth jaw restorations. The precision of restoration depends largely on the measurement accuracy of tooth jaw. Therefore, in this paper the three dimensional measurement system of tooth jaw based on grating projection is studied and main contents are as follows.
This paper describes the measurement principle and the approach used in the system and proposes the overall framework of the measurement system based on the idea of modular, which includes the tooth jaw positioning module, optical path adjustment module, the visual measurement module, product appearance modules, system calibration module, encoding and decoding modules, three-dimensional reconstruction of the module and point cloud merging module. Meanwhile, this paper gives some details on the selection of the instruments used in the measurement system and the design of the listed modules above, which provides the basic guarantee for the measurement system to achieve the function.
This paper studies calibration methods of camera and projector and compares the pros and cons of various calibration methods. On the basis of Zhang-Zhengyou calibration method widely used, the calibration method combined measurement objects and system characters is studied for application,which provides an important support for the overall accuracy of the system. It establishes a three-dimensional reconstruction model of non-geometric constraint, which makes a significant reduction of the demand of the precision of the system in the processing and assembly while the system may be relatively more stable.
In view of non-contact optical three dimensional measurement of tooth jaw, A jig design method which integrates the calibration function is proposed for realizing spatial coincidence during the process of objects to be measured and calibration target. The coordinate systems are defined monocular vision measurement process involved. A coordinate matching-based point clouds registration technology is proposed for simplifying the process of point clouds registration and simultaneously realizing the zero error of point clouds registration theory. With the experimental verification, cloud registration data with some precision is obtained, which significantly support the overall accuracy of dental measurement system.
The three dimensional measurement device in this article is used for tooth jaw measurement, the experimental process is stable, the period of single measurement is not more than 1 minute and a certain accuracy is achieved, which provides a digital measurement platform for CAD / CAM technology to access to the original point cloud. Meanwhile, the research in this article can be used for other objects to be measured with complex surface features, such as precision Measurement, Heritage, etc.
引文
[1]陈薇,顾志苓,张辉等.北京市中老年人牙齿缺失及修复情况分析.北京口腔医学, 2000, 8(4): 169~172.
[2]王宇,侯玮,陈薇等.北京市老年人口腔健康行为的抽样调查与分析.北京口腔医学, 2010, 18(1): 44~46.
[3]于皓,王贻宁.计算机辅助设计与计算机辅助制作技术在口腔修复中的应用.国际口腔医学杂志, 2008, 35(3) : 344~346.
[4]郑韵哲,吴琳,王勇.计算机辅助制作技术在口腔修复领域的应用.国际口腔医学杂志, 2008, 35(6): 704~708.
[5]刘大峰.基于点云的口腔修复体曲面测量与重建基础技术研究及应用: [博士学位论文].南京:南京航空航天大学, 2007.
[6]周星,高志军.立体视觉技术的应用与发展.工程图学学报, 2010, 4: 50~55.
[7] Gerd H., Jurgen M. Physical limits of 3D-sensing. SP IE, 1992, 1822: 150.
[8] Rainer G., Gerd H. Laser triangulation: fundamental uncertainly in distance measurement. App. Op t. , 1994, 33 (7) : 1306.
[9]郝煜栋,赵洋,李达成.光学投影式三维测量技术综述.光学技术, 1998, 5: 57~60.
[10]葛东东,王淮生,宋家友.光栅投影三维轮廓测量技术分析及进展.上海电力学院学报, 2005, 21(4): 378~382.
[11]李忠科,王勇,秦永元等.牙模激光三维扫描仪结构与标定方法研究.电子测量与仪器学报, 2004: 1096~1101.
[12]吴江,高勃,赵湘辉等.新型3DSSSTDⅡ结构光三维测量系统重建牙颌模型的可靠性对比研究.华西口腔医学杂志, 2008, 26(4): 448~451.
[13]张修银,杨宠莹,罗建平等.相位移法用于牙冠形状三维自动测量.上海生物医学工程杂志, 1994, 38(3): 46~47, 62.
[14]吴琳,李瑞,吕培军等.光栅投影技术在获取牙列缺损三维数据中的应用.华西口腔医学杂志, 2006, 24(3): 276~278.
[15]张修银,杨宠莹.数字散斑相关方法用于牙冠形状的三维测量.上海口腔医学, 1997, 6(2) : 68~70.
[16] Takasaki H. Morie topography. Applied Optics, 1970, 9(4) :942-948 .
[17]陈俊,吕培军,冯海兰等.牙颌模型三维激光扫描系统可靠性研究及与手工测量的比较.现代口腔医学杂志, 2000, 14(4): 251~253.
[18] Quimby M. L., Vig K. W., Rashid R. G., et al. The Accuracy and reliability of measurements made on computer-based digital models. Angle Orthod,2004, 74:298~303.
[19] Tomassetti J. J., Taloumis L.J., Denny J.M., et al. A comparison of 3 computerized bolton tooth-size analyses with a commonly used method. Angle Orthod, 2001, 71:351~357.
[20]刘松林,许天民,林久祥.三维数字化牙颌模型的数据采集方法和测量可靠性.口腔正畸学, 2008, 15(3): 137~140.
[21] Wang Q. L., Fu L., Liu Z.Z. Review on camera calibration. In: 2010 Chinese Control and Decision Conference: 3354~3358.
[22] A bdel-Aziz Y. I., Karara H. M. Direct linear transformation into object space coordinates in Close-Range Photogrammetry. In: Proc Symposium on Close-Range Photogrammetry, 1971: 1~18.
[23] Luh J. Y., Klaasen J. A. A three dimensional vision by off shelf system with multi-cameras. In: IEEE Transactions on Pattern Analysis and Machine Intelligence,1985 ,7 (1) : 35~45.
[24] Tsai R. Y. An efficient and accurate camera calibration technique for 3D machine vision. In: Proc CV PR’86: 364~374.
[25] Martins H. A., Birk J.R., Kelley R.B. Camera models based no data from two calibration planes. Computer Graphics and Imaging Processing, 1981, 17: 173~180.
[26] Zhang Z.Y. Flexible camera calibration by viewing a plane from unknown orientations. In: Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999: 663~673.
[27] Moons T., Van Gool L, Proesmans M, et al. Affine reconstruction from perspective image pairs with a relative object2camera translation in between. IEEE Transaction on Pattern Analysis and Machine Intelligence , 1996 , 18 (1) : 77~83.
[28] Triggs B. Auto2calibration and absolute quadric. In: Proceedings of Computer Vision and Pattern Recognition, 1997: 604~614.
[29] Ma S.D. A self-calibration technique for active vision system. IEEE Trans Robotics and Automation, 1996, 12(1): 114~134.
[30]李鹏,王军宁.摄像机标定方法综述.山西电子技术. 2007(4 ) : 77~79.
[31] Zhang Z.Y. A Flexible New Technique for Camera Calibration. Technical ReportMSRTR-98-71, Microsoft Research, 1998, 22(11): 1330~1334.
[32]吴敏,周来水,王占东等.测量点云数据的多视拼合技术研究.南京航空航天大学学报, 2003, 35(5): 552~557.
[33]苏志步.大尺寸测量的点云自动拼合技术研究:[硕士学位论文].武汉:华中科技大学, 2009.
[34]李必卿.点云多视图拼合研究与设计: [硕士学位论文].绵阳:西南科技大学, 2009.
[35]孙世为,王耕耘,李志刚.逆向工程中多视点云的拼合方法.计算机辅助工程, 2002, 11(1): 8~12.
[36]刘宇,熊有伦.基于法矢的点云拼合方法.机械工程学报, 2007, 43(8): 7~11.
[37]翟欢乐.基于几何特征的点云拼合研究: [硕士学位论文].武汉:华中科技大学, 2009.
[38] Li W.L., Yin Z.P., Huang Y.A., et al. 3D point-based registration algorithm based on adaptive distance function. IET Computer Vision, 2011, 5(1): 68~76.
[39]张广军.视觉测量.北京:科学出版社, 2008.
[40]毛剑飞,邹细勇,诸静.改进的平面模板两步法标定摄像机.中国图像图形学报, 2004, 9(7): 846-852.
[41] Tsai R. Y. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE Journal of Robotics and Automation, 1987, 3(4): 323~344.
[2]王宇,侯玮,陈薇等.北京市老年人口腔健康行为的抽样调查与分析.北京口腔医学, 2010, 18(1): 44~46.
[3]于皓,王贻宁.计算机辅助设计与计算机辅助制作技术在口腔修复中的应用.国际口腔医学杂志, 2008, 35(3) : 344~346.
[4]郑韵哲,吴琳,王勇.计算机辅助制作技术在口腔修复领域的应用.国际口腔医学杂志, 2008, 35(6): 704~708.
[5]刘大峰.基于点云的口腔修复体曲面测量与重建基础技术研究及应用: [博士学位论文].南京:南京航空航天大学, 2007.
[6]周星,高志军.立体视觉技术的应用与发展.工程图学学报, 2010, 4: 50~55.
[7] Gerd H., Jurgen M. Physical limits of 3D-sensing. SP IE, 1992, 1822: 150.
[8] Rainer G., Gerd H. Laser triangulation: fundamental uncertainly in distance measurement. App. Op t. , 1994, 33 (7) : 1306.
[9]郝煜栋,赵洋,李达成.光学投影式三维测量技术综述.光学技术, 1998, 5: 57~60.
[10]葛东东,王淮生,宋家友.光栅投影三维轮廓测量技术分析及进展.上海电力学院学报, 2005, 21(4): 378~382.
[11]李忠科,王勇,秦永元等.牙模激光三维扫描仪结构与标定方法研究.电子测量与仪器学报, 2004: 1096~1101.
[12]吴江,高勃,赵湘辉等.新型3DSSSTDⅡ结构光三维测量系统重建牙颌模型的可靠性对比研究.华西口腔医学杂志, 2008, 26(4): 448~451.
[13]张修银,杨宠莹,罗建平等.相位移法用于牙冠形状三维自动测量.上海生物医学工程杂志, 1994, 38(3): 46~47, 62.
[14]吴琳,李瑞,吕培军等.光栅投影技术在获取牙列缺损三维数据中的应用.华西口腔医学杂志, 2006, 24(3): 276~278.
[15]张修银,杨宠莹.数字散斑相关方法用于牙冠形状的三维测量.上海口腔医学, 1997, 6(2) : 68~70.
[16] Takasaki H. Morie topography. Applied Optics, 1970, 9(4) :942-948 .
[17]陈俊,吕培军,冯海兰等.牙颌模型三维激光扫描系统可靠性研究及与手工测量的比较.现代口腔医学杂志, 2000, 14(4): 251~253.
[18] Quimby M. L., Vig K. W., Rashid R. G., et al. The Accuracy and reliability of measurements made on computer-based digital models. Angle Orthod,2004, 74:298~303.
[19] Tomassetti J. J., Taloumis L.J., Denny J.M., et al. A comparison of 3 computerized bolton tooth-size analyses with a commonly used method. Angle Orthod, 2001, 71:351~357.
[20]刘松林,许天民,林久祥.三维数字化牙颌模型的数据采集方法和测量可靠性.口腔正畸学, 2008, 15(3): 137~140.
[21] Wang Q. L., Fu L., Liu Z.Z. Review on camera calibration. In: 2010 Chinese Control and Decision Conference: 3354~3358.
[22] A bdel-Aziz Y. I., Karara H. M. Direct linear transformation into object space coordinates in Close-Range Photogrammetry. In: Proc Symposium on Close-Range Photogrammetry, 1971: 1~18.
[23] Luh J. Y., Klaasen J. A. A three dimensional vision by off shelf system with multi-cameras. In: IEEE Transactions on Pattern Analysis and Machine Intelligence,1985 ,7 (1) : 35~45.
[24] Tsai R. Y. An efficient and accurate camera calibration technique for 3D machine vision. In: Proc CV PR’86: 364~374.
[25] Martins H. A., Birk J.R., Kelley R.B. Camera models based no data from two calibration planes. Computer Graphics and Imaging Processing, 1981, 17: 173~180.
[26] Zhang Z.Y. Flexible camera calibration by viewing a plane from unknown orientations. In: Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999: 663~673.
[27] Moons T., Van Gool L, Proesmans M, et al. Affine reconstruction from perspective image pairs with a relative object2camera translation in between. IEEE Transaction on Pattern Analysis and Machine Intelligence , 1996 , 18 (1) : 77~83.
[28] Triggs B. Auto2calibration and absolute quadric. In: Proceedings of Computer Vision and Pattern Recognition, 1997: 604~614.
[29] Ma S.D. A self-calibration technique for active vision system. IEEE Trans Robotics and Automation, 1996, 12(1): 114~134.
[30]李鹏,王军宁.摄像机标定方法综述.山西电子技术. 2007(4 ) : 77~79.
[31] Zhang Z.Y. A Flexible New Technique for Camera Calibration. Technical ReportMSRTR-98-71, Microsoft Research, 1998, 22(11): 1330~1334.
[32]吴敏,周来水,王占东等.测量点云数据的多视拼合技术研究.南京航空航天大学学报, 2003, 35(5): 552~557.
[33]苏志步.大尺寸测量的点云自动拼合技术研究:[硕士学位论文].武汉:华中科技大学, 2009.
[34]李必卿.点云多视图拼合研究与设计: [硕士学位论文].绵阳:西南科技大学, 2009.
[35]孙世为,王耕耘,李志刚.逆向工程中多视点云的拼合方法.计算机辅助工程, 2002, 11(1): 8~12.
[36]刘宇,熊有伦.基于法矢的点云拼合方法.机械工程学报, 2007, 43(8): 7~11.
[37]翟欢乐.基于几何特征的点云拼合研究: [硕士学位论文].武汉:华中科技大学, 2009.
[38] Li W.L., Yin Z.P., Huang Y.A., et al. 3D point-based registration algorithm based on adaptive distance function. IET Computer Vision, 2011, 5(1): 68~76.
[39]张广军.视觉测量.北京:科学出版社, 2008.
[40]毛剑飞,邹细勇,诸静.改进的平面模板两步法标定摄像机.中国图像图形学报, 2004, 9(7): 846-852.
[41] Tsai R. Y. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE Journal of Robotics and Automation, 1987, 3(4): 323~344.
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