相机与投影仪的标定是影响光栅投影三维测量系统精度的因素之一,且标定所得参数的精度直接影响系统的测量精度。分析标志点边缘成像时的退化模型,提出了基于高斯曲线拟合与边缘局部区域效应相结合的亚像素边缘检测方法,获取高精度边缘,提高标志点检测精度;使用基于透视变换图像矫正的标志点快速排序匹配方法,进行相机快速高精度标定。分析投影仪标定时的相位误差,提出了一种基于径向基的线性插值方式,提高标志点圆心相位获取精度。实验验证,使用上述亚像素边缘检测方式,标志点的边缘残差为0.0871,对比基于高斯曲线的拟合方式,精度提高了41%,相机标定重投影误差均值为0.0524像素;使用上述相位插值方式,投影仪标定重投影误差均值为0.1203像素,对比使用双线性插值方式,标定精度提高23.9%。
Abstract
The calibration of both camera and projector becomes the key element to decide the accuracy of 3D fringe projection measurement, and accuracy of parameter calibration directly affects accuracy of the measurement. By analyzing the imaging degradation model of mark points, a sub-pixel edge detection method was proposed to obtain the high-precision edges based on the combination of Gaussian curve fitting and edge partial area effect, and thus to improve the accuracy of mark point detection. A quick sort matching method of mark points was presented based on the image rectification technic by way of perspective transformation, and the high-precision camera calibration was finished rapidly. Furthermore, by analyzing the phase error in projector calibration, a linear interpolation method was proposed based on radial basis function in order to improve the phase accuracy of circle center of mark points. Then the experimental results show that the edge residual error of mark points is 0.087 1. Compared to the Gaussian curve fitting method, its accuracy is improved by 41%, the average re-projection errors of camera calibration is 0.052 4 pixels, and the re-projection error of projector is 0.120 3 pixels. Compared to the bi-linear interpolation method, its calibration accuracy is increased by 23.9%.
关键词
标定 /
亚像素边缘 /
局部区域效应 /
径向基函数 /
光栅投影
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Key words
grating projection /
partial area effect /
calibration /
radial basis function /
sub-pixel edge
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基金
国家自然科学基金(51775230);广西自然科学基金(2017GXNSFAA198313,2018GXNSFAA294003);桂林市科学研究与技术开发计划项目(20170104-2);广西高等学校千名中青年骨干教师培育计划资助项目
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参考文献
杨再华, 李玉和, 李庆祥, 等. 一种基于光学三角法的形貌测量系统[J]. 光学技术,2005(4):622-623, 626.
刘伟涛. 基于结构光投影的三维测量系统关键技术研究[D]. 桂林: 广西师范大学, 2018.
李长春. 机器视觉中摄像机标定技术研究及实现[D]. 南京: 南京航空航天大学, 2009.
朱统晶, 周平, 刘欣冉, 等. 结构光三维测量系统标定的关键算法研究[J]. 应用光学,2014,35(5):848-852.
张虎, 达飞鹏, 邢德奎. 光学测量中椭圆圆心定位算法研究[J]. 应用光学,2008,29(6):905-911.
朱勇建, 黄振, 马俊飞, 等. 基于改进多频条纹结构光的三维测量方法: 中国, 109489585A[P]. 2019-03-19.
毛翠丽, 卢荣胜. 提高多频条纹投影相位提取精度的反向误差补偿法[J]. 光学学报,2018,38(4):240-248.
郑东亮, 达飞鹏. 双步相移光栅投影测量轮廓术[J]. 光学学报,2012,32(5):94-100.
刘力双, 张铫, 卢慧卿, 等. 图像的快速亚像素
YANG Zaihua, LI Yuhe, LI Qingxiang, et al. Measuring profile system based on optical triangular method[J]. Optical Technique,2005(4):622-623, 626.
LIU Weitao. Research on key technology of 3D measurement system based on structured light projection[D]. Guilin: Guangxi Normal University, 2018.
LIU K. Real-time 3-D reconstruction by means of structured light illumin[D]. Kentucky: University of Kentucky, 2010.
LI Changchun. Study and realization of camera calibration technology in machine vision[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2009.
HO C T, CHEN L H. A fast ellipse/circle detector using geometric symmetry[J]. Pattern Recognition,1995,28(1):117-124.
FORNACIARI M, PRATI A, CUCCHIARA R. A fast and effective ellipse detector for embedded vision applications[J]. Pattern Recognition,2014,47(11):3693-3708.
LU C S, XIA S Y, SHAO M, et al. Arc-support line segments revisited: an efficient high-quality ellipse detection[J]. IEEE Transactions on Image Processing,2020,
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脚注
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