深度约束的零件尺寸测量系统标定方法

肖志涛; 朱莎莎; 耿磊; 李月龙; 刘文超; 叶琨

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深度约束的零件尺寸测量系统标定方法

肖志涛, 朱莎莎, 耿磊, 李月龙, 刘文超, 叶琨

文章导航 > 红外与激光工程 > 2015 > 44(9): 2831-2836

肖志涛, 朱莎莎, 耿磊, 李月龙, 刘文超, 叶琨. 深度约束的零件尺寸测量系统标定方法[J]. 红外与激光工程, 2015, 44(9): 2831-2836.

引用本文:

肖志涛, 朱莎莎, 耿磊, 李月龙, 刘文超, 叶琨. 深度约束的零件尺寸测量系统标定方法[J]. 红外与激光工程, 2015, 44(9): 2831-2836.

Xiao Zhitao, Zhu Shasha, Geng Lei, Li Yuelong, Liu Wenchao, Ye Kun. Calibration method for parts dimension measurement system based on depth constraint[J]. Infrared and Laser Engineering, 2015, 44(9): 2831-2836.

Citation:

Xiao Zhitao, Zhu Shasha, Geng Lei, Li Yuelong, Liu Wenchao, Ye Kun. Calibration method for parts dimension measurement system based on depth constraint[J]. Infrared and Laser Engineering, 2015, 44(9): 2831-2836.

深度约束的零件尺寸测量系统标定方法

1.
天津工业大学电子与信息工程学院,天津 300387;
2.
天津工业大学计算机科学与软件学院,天津 300387

基金项目:

国家自然科学基金(61102150,61302127,11326198);天津市科技支撑计划重点项目(13ZCZDGX02100,14ZCZDGX00033)

详细信息

作者简介:
肖志涛(1971-),男,教授,博士生导师,主要从事图像处理与模式识别方面的研究。Email:xiaozhitao@tjpu.edu.cn

通讯作者: 耿磊(1982-),男,副教授,硕士生导师,主要从事测试计量技术及仪器方面的研究。Email:genglei@tjpu.edu.cn

中图分类号: TP391

Calibration method for parts dimension measurement system based on depth constraint

1.
School of Electronics and Information Engineering,Tianjin Polytechnic University,Tianjin 300387,China;
2.
School of Computer Science & Software Engineering,Tianjin Polytechnic University,Tianjin 300387,China

摘要: 针对大尺寸平面零件尺寸测量系统标定精度不高的问题,提出了一种基于深度信息的系统标定方法。首先利用圆形平面靶标,提出一种提取靶标图像特征点的新方法,采用自适应阈值的边缘检测和多项式拟合算法提取特征点亚像素轮廓,利用椭圆拟合得到中心坐标;然后根据带有畸变的非线性成像几何模型,采用最小二乘法计算摄像机参数的最优解,获得靶标的位姿;最后提出被测物表面与靶标平面之间的深度信息作为摄像机模型修正项,校正测量平面位姿,利用成像原理和直线与零件表面交点确定零件尺寸。设计了单目视觉尺寸测量系统并进行实验,结果表明:标定反投影误差小于0.02 pixel,在10.75 m2的视场内,系统测量精度达到了0.05 mm。
- 零件尺寸测量 /
- 摄像机标定 /
- 特征点检测 /
- 深度约束
Abstract: A new algorithm of system calibration based on depth constraint was presented to improve the calibration accuracy of large scale planar part vision measurement system. Firstly, an algorithm of extracting the round marks of calibration plate was proposed. Sub-pixel contours of marks were extracted by edge detection algorithm based on adaptive threshold and polynomial fitting, then the center coordinates can be computed by ellipse fitting method. Then, on the basis of analyzing camera distortion model, the optimal solution of internal parameters and plate poses were obtained using least square method. Finally, the pose of measuring plane was transformed by depth information as a correction term between parts surface and calibration plate. The dimensions could be calculated using imaging principle and the intersection point of the line and the part surface. Measurement system was designed and experiments were carried out. The result shows that the calibration back-projection error is less than 0.02 pixel and the precision of the system is up to 0.05 mm in the range of 10.75 m2.
- part dimensional measurement /
- camera calibration /
- mark detection /
- depth constrain

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深度约束的零件尺寸测量系统标定方法

1. 天津工业大学电子与信息工程学院,天津 300387;

2. 天津工业大学计算机科学与软件学院,天津 300387

作者简介:
肖志涛(1971-),男,教授,博士生导师,主要从事图像处理与模式识别方面的研究。Email:xiaozhitao@tjpu.edu.cn

通讯作者: 耿磊(1982-),男,副教授,硕士生导师,主要从事测试计量技术及仪器方面的研究。Email:genglei@tjpu.edu.cn

收稿日期: 2015-01-05
修回日期: 2015-02-08
刊出日期: 2015-09-25

基金项目:

国家自然科学基金(61102150,61302127,11326198);天津市科技支撑计划重点项目(13ZCZDGX02100,14ZCZDGX00033)

中图分类号: TP391

关键词:

摘要: 针对大尺寸平面零件尺寸测量系统标定精度不高的问题,提出了一种基于深度信息的系统标定方法。首先利用圆形平面靶标,提出一种提取靶标图像特征点的新方法,采用自适应阈值的边缘检测和多项式拟合算法提取特征点亚像素轮廓,利用椭圆拟合得到中心坐标;然后根据带有畸变的非线性成像几何模型,采用最小二乘法计算摄像机参数的最优解,获得靶标的位姿;最后提出被测物表面与靶标平面之间的深度信息作为摄像机模型修正项,校正测量平面位姿,利用成像原理和直线与零件表面交点确定零件尺寸。设计了单目视觉尺寸测量系统并进行实验,结果表明:标定反投影误差小于0.02 pixel,在10.75 m2的视场内,系统测量精度达到了0.05 mm。

English Abstract

Calibration method for parts dimension measurement system based on depth constraint

1. School of Electronics and Information Engineering,Tianjin Polytechnic University,Tianjin 300387,China;

2. School of Computer Science & Software Engineering,Tianjin Polytechnic University,Tianjin 300387,China

Received Date: 2015-01-05
Rev Recd Date: 2015-02-08
Publish Date: 2015-09-25

Keywords:

Abstract: A new algorithm of system calibration based on depth constraint was presented to improve the calibration accuracy of large scale planar part vision measurement system. Firstly, an algorithm of extracting the round marks of calibration plate was proposed. Sub-pixel contours of marks were extracted by edge detection algorithm based on adaptive threshold and polynomial fitting, then the center coordinates can be computed by ellipse fitting method. Then, on the basis of analyzing camera distortion model, the optimal solution of internal parameters and plate poses were obtained using least square method. Finally, the pose of measuring plane was transformed by depth information as a correction term between parts surface and calibration plate. The dimensions could be calculated using imaging principle and the intersection point of the line and the part surface. Measurement system was designed and experiments were carried out. The result shows that the calibration back-projection error is less than 0.02 pixel and the precision of the system is up to 0.05 mm in the range of 10.75 m2.