In reverse engineering, reconstruction of 3D point cloud data is the key step to acquire the final profile of the object. However, the quality of 3D reconstruction is influenced by noise in the three-dimensional measurement. This paper aims to tackle the issue of removing the noisy data from the complex point cloud data. The 3D-GPF (Three Dimensional Global Phase Filtering) global phase filtering method is proposed based on the study of phase filtering method, consisting of the steps below. Firstly, the six-step phase shift profilometry is used to obtain the local phase information, and encoding the obtained phase information. Through the global phase unwrapping method, the global phase can be acquired. Secondly, 3D-GPF method is used for the obtained global phase. Finally, the effect of 3D reconstruction is analyzed after the global phase filtering. Experimental results indicate that the noisy points of three-dimensional graphics is reduced 98.02%, the speed of 3D reconstruction is raised 12%.The effect of the proposed global phase filtering method is better than DCT and GSM methods. It is high precision and fast speed, and can be widely used in other 3D reconstruction application.
The registration of point cloud is important for large object measurement. A measurement method for coordinate system transformation based on robot is proposed in this paper. Firstly, for obtaining extrinsic parameters, the robot moves to three different positions to capture the images of three targets. Then the transformation matrix X between camera and tool center point (TCP) coordinate systems can be calculated by using the known parameters of robot and the extrinsic parameters, and finally the multi-view coordinate system can be transformed into robot coordinate system by the transformation matrix X. With the help of robot, the multi-view point cloud can be easily transformed into a unified coordinate system. By using robot, the measurement doesn't need any mark. Experimental results show that the method is effective.
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