结构光测量系统中多视点云自动拼合算法

从结构光测量系统的实际测量需要出发，提出一种向待测物体表面粘贴参考点，从而利用参考点信息来自动拼合不同视角点云数据的算法。该算法首先采用一种改进的区域识别与最小二乘法相结合的方法准确提取参考点形心，并根据计算机视觉理论求解出参考点的三维坐标，然后根据参考点的空间特征不变量，提出了参考点快速匹配算法，从而获得不同视角中的参考点对应关系，最后采用四元数分解算法求解出旋转与平移矩阵，实现了点云的自动拼合。实验结果验证了该算法的有效性及实用性。

Automatic multi-view point cloud merging algorithm used in structure light measure system

An automatic multi-view point cloud merging algorithm for structure light measure system was presented. Firstly, an improved region identification integrated with least-squares algorithm was used to compute the center of the reference point accurately, and the 3D coordinate of the reference point was ascertained through the theory of machine vision. Then, based on the invariability of spatial character, a rapid reference point matching algorithm was put forward to acquire the corresponding relationship between the reference points with different visual angles. Lastly, the rotation matrix and translation matrix were computed by quaternion decompose algorithm to carry out the automatic multi-view point cloud merging algorithm. The result of the experiments shows the validity and great practicability of the algorithm.