基于计算机视觉的板类零件曲面测量系统

利用计算机视觉原理，建立了板类零件曲面测量系统，该系统首先根据人眼感知事物原理，采用神经网络来拟合图像坐标与空间坐标的映射关系；然后以光栅投影条纹为特征，用小波变换提取条纹边缘，在此基础上，提出搜索式无监督聚类方法，使带状离散边缘点按边缘实际分布情况分为不同组群，并将各组边缘点分别拟合成连续B样条曲线，同时结合视觉几何不变性，实现了亚象素级的立体精匹配；接着，运用小波分解来讲接图象，融合数据，并由图象坐标与空间坐标的映射关系，求解曲面上点的空间坐标，测量精度可控制在0．5mm/m以内。

Surface Measurement System of Sheet Metal Parts Based on Computer Vision

On the basic of computer vision principle, a surface measurement system of sheet metal parts is proposed in this paper. Using neural network, the mapping relation between image points and special points is established. Some distorted stripes are obtained on surface, and the points of stripe edges are detected by wavelet edge detection. A searching non supervisor clustering algorithm is discussed, so all of edge points are divided into different groups according to stripe edge situation, the edge points of every group are fitted into a B spline curve. The curves are recognized and marked based on geometric invariance to search corresponding points at sub pixel level. Furthermore, the multi scale and multi resolution attributes of wavelet are applied to image mosaic and data integration, so a large scale surface can be measured. At last the coordinates of points on surface are calculated with the mapping relation between image points and special points, and the measuring precision is less than 0 5mm/m.The system avoid emending optical system distortion of cameras, achieve stereo matching at sub|pixel level, and integrate surface data, so the large surface can be able to measure.