双摄像机模组的组合式标定和校正方法
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摘要
提出了双摄像机模组的组合式标定和校正方法,能够将传统的标定和校正2道工序合并为1道工序,不需要借助于外部测量设备,仅利用双摄像机同时对目标模板拍摄的1幅图像,即可实现双摄像机模组的标定和校正。先基于交比不变性计算摄像机的径向畸变系数,将摄像机畸变成像模型转换为线性模型,利用线性模型分别对2个摄像机进行标定;然后计算2个摄像机之间的位姿偏移参数,调节右摄像机位姿,进行双摄像机之间的位姿校正;最后标定2个摄像机之间的位姿参数。实际应用结果表明,所提出的双摄像机模组校正和标定方法,校正和标定精度高,缩短了工艺时间,提高了工艺效率,能够满足双摄像机模组封装生产工艺的要求。
We propose a combined calibration and correction method for dual-camera module, which can merge the two processes of traditional calibration and correction into one procedure. The calibration and correction of the dual-camera module does not rely on external measuring devices, and only requires a picture of the target template by the two cameras simultaneously. Firstly, we calculate the radial distortion coefficient of the camera based on cross-ratio invariance, and transform the camera distortion imaging model into a linear model by which the two cameras are respectively calibrated. Then the pose offset parameters between the two cameras are calculated, the right camera position is adjusted, and the pose correction between the two cameras is achieved. Finally, the pose parameters between the two cameras are calibrated. Actual application results show that the proposed calibration and correction method for dual-camera module has high precision, shortens the processing time, improves the processing efficiency, and can satisfy the requirements of packaging and production technology of dual-camera modules.
We propose a combined calibration and correction method for dual-camera module, which can merge the two processes of traditional calibration and correction into one procedure. The calibration and correction of the dual-camera module does not rely on external measuring devices, and only requires a picture of the target template by the two cameras simultaneously. Firstly, we calculate the radial distortion coefficient of the camera based on cross-ratio invariance, and transform the camera distortion imaging model into a linear model by which the two cameras are respectively calibrated. Then the pose offset parameters between the two cameras are calculated, the right camera position is adjusted, and the pose correction between the two cameras is achieved. Finally, the pose parameters between the two cameras are calibrated. Actual application results show that the proposed calibration and correction method for dual-camera module has high precision, shortens the processing time, improves the processing efficiency, and can satisfy the requirements of packaging and production technology of dual-camera modules.
引文
[1] Zhuang Guang-ming,Cui Jian-wei,Peng Zuo-xiang.Calculation of system demarcation based on binocular location[J].Computer Engineering and Applications,2010,46(8):45-47.(in Chinese)
[2] Zhang Kui,Chen Zhao-xue,Zhao Hang,et al.Research on binocular camera calibration based on two groups of concentric circle points[J].Optical Technique,2016,42(3):197-203.(in Chinese)
[3] Yan He,Wu Bin.Improved neural network for binocular camera calibration[J].Journal of Southwest University of Science and Technology,2013,28(4):66-71.(in Chinese)
[4] Chen Tian-fei,Zhao Ji-bin,Wu Xiang.New calibration method for line structure light sensor based on planar target[J].Acta Optica Sinica,2015,35(1):0112004.(in Chinese)
[5] Kong Xiao-fang,Chen Qian,Gu Guo-hua,et al.GPS-based binocular camera calibration and space coordinate reconstruction[J].Optics and Precision Engineering,2017,25(2):485-492.(in Chinese)
[6] Tang Qiu-hu,Zhang Zhi-yi.Camera self-calibration based on multiple view images[J].Computer Engineering & Science,2017,39(4):748-756.(in Chinese)
[7] Wang Xiu-ping,Bai Rui-lin,Liu Zi-teng.A novel approach for determining intrinsic parameters of camera using two parallelograms[J].Journal of Shanghai Jiao Tong University,2015,49(3):366-371.(in Chinese)
[8] Xue Jun-peng,Su Xian-yu.Camera calibration with signal image based on two orthogonal one-dimensional objects[J].Acta Optica Sinica,2012,32(1):115001.(in Chinese)
[9] Zhang Min,Jin Long-xu,Li Guo-ning,et al.Camera distortion calibration method based on straight line charateristics[J].Acta Optica Sinica,2015,35(6):615001.(in Chinese)
[10] Ye Feng,Wang Min,Chen Jian-dong,et al.Camera nonlinear distortion correction based on coplanar points[J].Optics and Precision Engineering,2015,23(10):2962-2970.(in Chinese)
[11] Liang Ling-fei.Distortion calibration method for linear cameras based on cross ratio and spacing ratio invariability[J].Science Technology and Engineering,2014,14(14):248-252.(in Chinese)
[12] Wang Jian-hua,Feng Fan,Liang Wei,et al.Non-linear model based camera calibration[J].Optoelectronic Technology,2012,32(1):33-39.(in Chinese)
[13] Li Huan-huan,Huang Shan,Zhang Hong-bin.The automatic image mosaic based on Harris and SIFT algorithms[J].Computer Engineering & Science,2012,34(11):104-109.(in Chinese)附中文参考文献:
[1] 庄光明,崔建伟,彭作详.基于双目定位原理的系统标定算法[J].计算机工程与应用,2010,46(8):45-47.
[2] 张奎,陈兆学,赵航,等.基于两组同心圆环点的双目摄像机标定方法研究[J].光学技术,2016,42(3):197-203.
[3] 延和,吴斌.基于改进型神经网络的双目摄像机标定[J].西南科技大学学报,2013,28(4):66-71.
[4] 陈天飞,赵吉宾,吴翔.基于共面靶标的线结构光传感器标定新方法[J].光学学报,2015,35(1):112004.
[5] 孔筱芳,陈钱,顾国华,等.GPS双目摄像机标定及空间坐标重建[J].光学精密工程,2017,25(2):485-492.
[6] 唐秋虎,张志毅.基于多视图像的摄像机自标定方法[J].计算机工程与科学,2017,39(4):748-756.
[7] 王秀平,白瑞林,刘子腾.由任意平行四边形确定摄像机内参数的方法[J].上海交通大学学报,2015,49(3):366-371.
[8] 薛俊鹏,苏显渝.基于两个正交一维物体的单幅图像相机标定[J].光学学报,2012,32(1):115001.
[9] 张敏,金龙旭,李国宁,等.基于直线特征的摄像机镜头畸变标定方法[J].光学学报,2015,35(6):615001.
[10] 叶峰,王敏,陈剑东,等.共面点的摄像机非线性畸变校正[J].光学精密工程,2015,23(10):2962-2970.
[11] 梁灵飞.基于交比不变和间距比不变的线阵相机畸变标定方法[J].科学技术与工程,2014,14(14):248-252.
[12] 王建华,冯帆,梁伟,等.非线性模型下的摄像机标定[J].光电子技术,2012,32(1):33-39.
[13] 李欢欢,黄山,张洪斌.基于Harris与SIFT算法的自动图像拼接[J].计算机工程与科学,2012,34(11):104-109.
[2] Zhang Kui,Chen Zhao-xue,Zhao Hang,et al.Research on binocular camera calibration based on two groups of concentric circle points[J].Optical Technique,2016,42(3):197-203.(in Chinese)
[3] Yan He,Wu Bin.Improved neural network for binocular camera calibration[J].Journal of Southwest University of Science and Technology,2013,28(4):66-71.(in Chinese)
[4] Chen Tian-fei,Zhao Ji-bin,Wu Xiang.New calibration method for line structure light sensor based on planar target[J].Acta Optica Sinica,2015,35(1):0112004.(in Chinese)
[5] Kong Xiao-fang,Chen Qian,Gu Guo-hua,et al.GPS-based binocular camera calibration and space coordinate reconstruction[J].Optics and Precision Engineering,2017,25(2):485-492.(in Chinese)
[6] Tang Qiu-hu,Zhang Zhi-yi.Camera self-calibration based on multiple view images[J].Computer Engineering & Science,2017,39(4):748-756.(in Chinese)
[7] Wang Xiu-ping,Bai Rui-lin,Liu Zi-teng.A novel approach for determining intrinsic parameters of camera using two parallelograms[J].Journal of Shanghai Jiao Tong University,2015,49(3):366-371.(in Chinese)
[8] Xue Jun-peng,Su Xian-yu.Camera calibration with signal image based on two orthogonal one-dimensional objects[J].Acta Optica Sinica,2012,32(1):115001.(in Chinese)
[9] Zhang Min,Jin Long-xu,Li Guo-ning,et al.Camera distortion calibration method based on straight line charateristics[J].Acta Optica Sinica,2015,35(6):615001.(in Chinese)
[10] Ye Feng,Wang Min,Chen Jian-dong,et al.Camera nonlinear distortion correction based on coplanar points[J].Optics and Precision Engineering,2015,23(10):2962-2970.(in Chinese)
[11] Liang Ling-fei.Distortion calibration method for linear cameras based on cross ratio and spacing ratio invariability[J].Science Technology and Engineering,2014,14(14):248-252.(in Chinese)
[12] Wang Jian-hua,Feng Fan,Liang Wei,et al.Non-linear model based camera calibration[J].Optoelectronic Technology,2012,32(1):33-39.(in Chinese)
[13] Li Huan-huan,Huang Shan,Zhang Hong-bin.The automatic image mosaic based on Harris and SIFT algorithms[J].Computer Engineering & Science,2012,34(11):104-109.(in Chinese)附中文参考文献:
[1] 庄光明,崔建伟,彭作详.基于双目定位原理的系统标定算法[J].计算机工程与应用,2010,46(8):45-47.
[2] 张奎,陈兆学,赵航,等.基于两组同心圆环点的双目摄像机标定方法研究[J].光学技术,2016,42(3):197-203.
[3] 延和,吴斌.基于改进型神经网络的双目摄像机标定[J].西南科技大学学报,2013,28(4):66-71.
[4] 陈天飞,赵吉宾,吴翔.基于共面靶标的线结构光传感器标定新方法[J].光学学报,2015,35(1):112004.
[5] 孔筱芳,陈钱,顾国华,等.GPS双目摄像机标定及空间坐标重建[J].光学精密工程,2017,25(2):485-492.
[6] 唐秋虎,张志毅.基于多视图像的摄像机自标定方法[J].计算机工程与科学,2017,39(4):748-756.
[7] 王秀平,白瑞林,刘子腾.由任意平行四边形确定摄像机内参数的方法[J].上海交通大学学报,2015,49(3):366-371.
[8] 薛俊鹏,苏显渝.基于两个正交一维物体的单幅图像相机标定[J].光学学报,2012,32(1):115001.
[9] 张敏,金龙旭,李国宁,等.基于直线特征的摄像机镜头畸变标定方法[J].光学学报,2015,35(6):615001.
[10] 叶峰,王敏,陈剑东,等.共面点的摄像机非线性畸变校正[J].光学精密工程,2015,23(10):2962-2970.
[11] 梁灵飞.基于交比不变和间距比不变的线阵相机畸变标定方法[J].科学技术与工程,2014,14(14):248-252.
[12] 王建华,冯帆,梁伟,等.非线性模型下的摄像机标定[J].光电子技术,2012,32(1):33-39.
[13] 李欢欢,黄山,张洪斌.基于Harris与SIFT算法的自动图像拼接[J].计算机工程与科学,2012,34(11):104-109.