基于线激光与模板匹配的工件表面平坦度测量
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摘要
为了解决2D视觉对工件表面平坦度测量力不足,而现有的3D测量设备价格昂贵且缺乏定制灵活度的问题,提出了基于线激光与三维模板匹配的3D平坦度测量系统。首先,根据线激光、3D相机、拍摄材料以及运动平台,设计基于激光三角测量法的3D图像采集模块。然后利用3D图像与2D图像差异,根据第三维数据的特征,将三维点云数据分解为一系列二维图形,逐层匹配后再集成为3D模板,形成3D模板匹配模块。最后,根据匹配结果区域的第三维数据差,计算出材料目标区域的平坦度。实验结果显示:与当前2D视觉测量技术相比,所提方案对3D工件表面的定位与平坦度测量具有更高的精度。
In order to solve the problem that 2D vision is lack of flatness measurement, and the integrated 3D measurement system is expensive and lack of customized flexibility, a 3D flatness measurement system based on line laser and 3D template matching is proposed. First, according to the line laser, 3D camera, shooting material and motion platform, the 3D image acquisition module based on laser triangulation is designed. Then the difference between 3D images and 2D images is analyzed, according to the characteristics of the third dimension data, the 3D point cloud data is decomposed into a series of two-dimensional graphics, and then the 3D template matching module is designed after the layer matching is integrated into the 3D template. Finally, the flatness of the material target region is calculated according to the difference of the third dimension data. The experimental results show that compared with the traditional technology, the algorithm system has higher accuracy and measurement ability for the 3D object positioning and flatness measurement.
In order to solve the problem that 2D vision is lack of flatness measurement, and the integrated 3D measurement system is expensive and lack of customized flexibility, a 3D flatness measurement system based on line laser and 3D template matching is proposed. First, according to the line laser, 3D camera, shooting material and motion platform, the 3D image acquisition module based on laser triangulation is designed. Then the difference between 3D images and 2D images is analyzed, according to the characteristics of the third dimension data, the 3D point cloud data is decomposed into a series of two-dimensional graphics, and then the 3D template matching module is designed after the layer matching is integrated into the 3D template. Finally, the flatness of the material target region is calculated according to the difference of the third dimension data. The experimental results show that compared with the traditional technology, the algorithm system has higher accuracy and measurement ability for the 3D object positioning and flatness measurement.
引文
[1]刘聪.二维多相机全场数字图像相关变形测量方法[J].光学学报,2016,37(17):76-79.Liu C.Two Dimensional Multi Camera Full Field Digital Image Correlation Deformation Measurement Method[J].Journal of Optics,2016,37(17):76-79.
[2]Soleiman Hosseinpour.Computer Vision System for In-Line Monitoring of Visual Texture Kinetics during Shrimp[J].Drying Technology,2015,33(2):238-254.
[3]Yunchao Wu,Keyi Xing,Jianchao Luo.Robust Deadlock Control for Automated Manufacturing Systems with an Unreliable Resource[J].Information Sciences,2016,346(10):17-28.
[4]Júlio Costa,Celina P.Le?o.Industrial Network Platform for Monitoring and Control of Automated Manufacturing Systems[J].IFAC Proceedings Volumes,2010,43(4):168-173.
[5]李江平.基于机器视觉的大尺寸密封圈全自动测量方法[J].计算机应用研究,2016,32(6):11-16.Li J.Automatic Measuring Method of Large Size Seal Ring Based on Machine Vision[J].Computer Application Research,2016,32(6):11-16.
[6]陈芳.结合3D测头和宏程序实现机床定位精度自动测量[J].组合机床与自动化加工技术,2016,12(10):124-127.Chen F.Automatic Measurement of Machine Tool Positioning Accuracy with 3D Probe and Macro Program[J].Combined machine tool and automatic machining technology,2016,12(10):124-127.
[7]李优新.机器人无标定视觉伺服系统的多种智能控制方法研究[D].中山:华南理工大学,2010.Li Y X.Research on multiple intelligent control methods for Robot Uncalibrated Visual Servo System[J].Zhongshan:South China University of Technology,2010.
[8]Raafat,Hazem M,Tolba,A S.Homoscedasticity for defect detection in homogeneous flat surface products[J].Textile Research Journal,2015,85(8):850-866.
[9]Ming-Hung Chiu,Yen-Hsin Chen,Jian-Ming Su.A New 3D Surface Profile Measuring System Based on the Telescope and Webcam[J].Natural Science,2014,6(16):1253-1258.
[10]Joshua C.Thurow.The defeater version of Benacerraf’s problem for a priori knowledge[J].Syntheses,2013,190(9):1587-1603.
[11]马旭,程咏梅,郝帅.面向未知区域深度测量的序列图像稠密点特征生成算法[J].航空学报,2015,36(2):596-604.Ma X,Cheng Y X,Hao S.Dense point feature generation algorithm for sequence image of unknown region depth measurement[J].Journal of Aeronautics,2015,36(2):596-604.
[2]Soleiman Hosseinpour.Computer Vision System for In-Line Monitoring of Visual Texture Kinetics during Shrimp[J].Drying Technology,2015,33(2):238-254.
[3]Yunchao Wu,Keyi Xing,Jianchao Luo.Robust Deadlock Control for Automated Manufacturing Systems with an Unreliable Resource[J].Information Sciences,2016,346(10):17-28.
[4]Júlio Costa,Celina P.Le?o.Industrial Network Platform for Monitoring and Control of Automated Manufacturing Systems[J].IFAC Proceedings Volumes,2010,43(4):168-173.
[5]李江平.基于机器视觉的大尺寸密封圈全自动测量方法[J].计算机应用研究,2016,32(6):11-16.Li J.Automatic Measuring Method of Large Size Seal Ring Based on Machine Vision[J].Computer Application Research,2016,32(6):11-16.
[6]陈芳.结合3D测头和宏程序实现机床定位精度自动测量[J].组合机床与自动化加工技术,2016,12(10):124-127.Chen F.Automatic Measurement of Machine Tool Positioning Accuracy with 3D Probe and Macro Program[J].Combined machine tool and automatic machining technology,2016,12(10):124-127.
[7]李优新.机器人无标定视觉伺服系统的多种智能控制方法研究[D].中山:华南理工大学,2010.Li Y X.Research on multiple intelligent control methods for Robot Uncalibrated Visual Servo System[J].Zhongshan:South China University of Technology,2010.
[8]Raafat,Hazem M,Tolba,A S.Homoscedasticity for defect detection in homogeneous flat surface products[J].Textile Research Journal,2015,85(8):850-866.
[9]Ming-Hung Chiu,Yen-Hsin Chen,Jian-Ming Su.A New 3D Surface Profile Measuring System Based on the Telescope and Webcam[J].Natural Science,2014,6(16):1253-1258.
[10]Joshua C.Thurow.The defeater version of Benacerraf’s problem for a priori knowledge[J].Syntheses,2013,190(9):1587-1603.
[11]马旭,程咏梅,郝帅.面向未知区域深度测量的序列图像稠密点特征生成算法[J].航空学报,2015,36(2):596-604.Ma X,Cheng Y X,Hao S.Dense point feature generation algorithm for sequence image of unknown region depth measurement[J].Journal of Aeronautics,2015,36(2):596-604.