Research On Segmentation Method Of Model With Complex Curved Surface Structure Based On Multi-view Region Growing

With the development of reverse engineering technology and computer graphics technology,it has been widely used in the design and manufacture of model with complex curved surface structure.The introduction of new technologies has accelerated the digitalization of the model.The digitized model can be used for feature analysis and shape detection to realize the process from solid model to design drawing.Among them,point cloud segmentation is the key content in the process of reverse design and manufacture,which is very important for the tasks of object classification,target recognition,3D reconstruction and so on.Many segmentation methods have been successfully applied to model with complex curved surface structure.However,because of the complexity and variety of model,it is difficult to define the boundary of some free-form surfaces.In addition,noise is mixed in the point cloud data obtained by scanning equipment,which causes some interference to the point cloud data processing.Therefore,the problem of poor recognition effect of some feature regions is common in the actual segmentation experiment.In order to improve the completeness of segmentation,a segmentation method based on multi-view region growing is proposed.The main research contents include:(1)Aiming at the characteristics of large volume of data and high complexity of the model,an initial classification method based on the principle of normal vector differences is proposed.The triangular mesh structure of model with complex curved surface structure is constructed based on G2S(Gabriel2 Simplex)criterion to obtain the topological features.The normal vector information of each triangular in the topology is calculated and corrected,and the model is divided into subregion of different categories based on the difference of normal vector direction between different categories.(2)Aiming at the lack of feature information from a single view and the defects of traditional distance image,a multi-view distance image generation method is proposed.All categories of point cloud are mapped vertically to 2D plane from the selected angle of view for grid division and grid assignment.The smoothing algorithm based on image morphology is introduced to weaken the sharp areas in the image,and then distance images under different angles of view are obtained.(3)In view of the low automation and insufficient segmentation integrity of traditional region growing algorithm,an improved region growing algorithm is proposed.Seed points in different feature regions in 3D space are calculated based on multi-view distance image.The region growing algorithm with constraints of grid normal vector offset angle and distance is used to identify different feature surfaces,and the KNN(K-Nearest Neighbor,KNN)algorithm is used to eliminate off-group points.The reasonable segmentation result of not less than 80% can be obtained on various models with complex curved surface structure.