针对视觉测量系统存在复杂系统误差的特点, 提出一种基于直线成像特征的系统综合标定方法, 有效地保证了测量精度。该方法通过对1等量块的平行直线边缘提取, 建立量块边缘空间物点位置和像点位置的原始对应关系, 利用量块边缘的理想直线特征, 通过统计计算对测量系统进行综合标定, 建立描述空间物点位置和像点位置的相互对应关系的二元三次标定函数。对在测量范围内不同方位的量块进行多次测量, 表明使用这种标定方法标定的视觉测量系统的测量精度能够达到。
Aimed at the features of various system errors in vision measuring system, the paper proposed a comprehensive system calibration method based on linear imaging characteristics with measurement accuracy, According to the extraction of parallel linear edges of 1 grade gauge blocks, the original correspondence between the space point positions and the image point positions of the edges is built.Using the ideal linear features of gauge block edges, comprehensive calibration of measurement system is carried out through statistical calculation, and a two-parameter second-order polynomial which describes the corresponding relation between the space point positions and the image point positions is established.Adopting the general engineering gauge block as the calibration tool, the calibration method is simple to operate and is easy to realize and has good versatility.It can comprehensively correct all kinds of system errors such as the optical distortion, the perspective error, the sensor position error and location error of edge detection algorithm.Bythe calibration method, multiple measurement experiments of different azimuth gauge blocks in the field show that the precision of the measurement system can reach.
[1]于起峰, 尚洋.摄像测量学原理与应用研究[M].北京:科学出版社, 2007.
[2]郭羽, 杨红, 杨照金, 等.CCD摄像系统镜头的畸变测量[J].应用光学, 2008, 29(2):279-282.
[3]郁春潮, 陈韶华.广角镜头的摄像机非线性标定技术[J].湖北大学学报(自然科学版), 2005, 27(4):351-354.
[4] 王子亨, 穆森, 邱桂苹.摄像机非线性标定方法[J].计算机工程与设计, 2010, 31(15):3526-3529.
[5]张玉发, 孙晓泉.一种基于同心圆环的图像畸变校正方法[J].光电技术应用, 2007, 22(2):63-65.
[6]朱日红, 李建欣.光学成像系统中非线性畸变的数字校正方法[J].南京理工大学学报, 2004, 28(4):414-416.
[7]朱铮涛, 黎绍发.镜头畸变及其校正技术[J].光学技术, 2005, 31(1):136-138.
[8]周富强, 胡坤, 张广军.基于共线特征点的摄像机镜头畸变校正[J].机械工程学报, 2006, 42(9):174-177.
[9]孙双花.视觉测量关键技术及在自动检测中的应用[D].天津:天津大学, 2007.