Feature Analysis and Automatic Extraction for the 3D Point Cloud of the Sanitary Wares Body

Abstract

The determination of the type of Sanitary Wares Body (SWB) is the premise for glazing robot to intelligently choose the glazing operation mode. Traditional judgement is to sample SWB by the camera with Charge Coupled Device (CCD), however, it is necessary to build a dark room to overcome the influence of light and environment, which leads to expansion of production space and increasement of cost. For the purpose of getting over the complex circumstances, a new method for automatic extraction of the feature based on three-dimensional (3D) point cloud for SWB is put forward, which is lower demand to the light environment than two-dimensional (2D) image. There are three parts for this method: Firstly, five feature parameters of the appearance of SWB were analyzed such as length-width ratio and the number of the holes. Then after the point cloud data of SWB was captured by depth camera, preprocessing, segmentation, and projection to flat space were carried out. In the end, automatic extraction of feature parameters from grey scale image was accomplished. The experiment result showed that the parameters from point cloud were basically consistent with those from the product of sanitary wares. The approach may reduce the illumination requirement and save the production cost; Therefore, it is feasible to improve the intelligent level of ceramics process.