基于空间平均的三维激光检测数据点的面分类

The Surface Classification of 3D Point Data Based on Spacial Averaging for Small Objects Using 3D Laser Inspection System

介绍了一个用于检查物体的系统,以及从一大堆点中找到为具有平面的物体进行面分类的方法.该系统基于光电技术,采用非接触式的方式进行测量.该系统是为尺寸小于2cm×2cm×2cm的小物体设计的,在利用镜面转台进行直线扫描的同时,物体在转台上作沿圆周不断的转动.在获得了三维物体的表面轮廓以后,运用一种几何方法进行划分.系统的性能体现在对不同大小的物体的测试上.

The system used to inspect objects and the method used to classify the surfaces for those objects with planar faces from a huge set of cloudy points are discussed. The systems are based on opto electronic techniques and hence are non contact. The system is designed for a small objects less than 2 cm×2 cm×2 cm. The surface classification resolution is based on the principle of spacial geometry of vectors direction in our coordinate system. The system can be considered scanning linearly with a rotation stage of a mirror. The object circumferentially rotates on a turntable. After obtained surface profile of 3D objects, we apply a geometrical method to classify the surfaces. The performance of the systems is demonstrated with different sizes of test objects.