视觉测量中基于距离相对约束的优化算法

Distance constraint-based optimization algorithm in videogrammetry

提出了一种新的基于距离相对约束的优化算法,该算法通过附加视场边缘距离约束条件较好地实现了对透镜畸变的纠正,提高了空间面形测量的精度.利用视场边缘相对控制点间空间距离固定以及像点坐标值残余误差平方和最小构建新的目标函数,并计算相应的法方程,经过数次迭代后可获得测量系统的方位参数和测量点的空间坐标,完成空间物体3D面形测量.对距离控制场的测量实验证明,该算法特别适用于大尺寸面形的测量,在3 m×4 m×1 m的测量视场内,根据该算法建立的视觉测量系统其最大测量偏差小于0.5mm,可满足大尺寸面形的测量要求.

A new optimization algorithm based on the distance constraint in videogrammetry system is presented in this paper. The image distortion can be corrected in this way and it can also largely improve the measurement system accuracy. A new objective function composed of the distance constraint and minimum of the sum of the squares of residuals is designed, and its corresponding normal equation is built. The orientation parameters and 3D coordinates of object points are computed simultaneously after several iterative by normal equation. The experiment results indicated that this algorithm could largely improve the measurement system accuracy; the absolute accuracy about 0. 5 mm can be achieved in the test filed of 3 m × 4 m ×1 m, it can satisfy the demand of the large-scale profile measurement.