Point cloud registration method based on feature extraction

Abstract

The invention belongs to the field of three-dimensional measurement, and particularly discloses a point cloud registration method based on feature extraction. The point cloud registration method comprises the steps: firstly calculating a feature index of each point through the maximum principal curvature and the minimum principal curvature of each point in a reference point cloud and a target point cloud; determining a neighborhood point of each point according to a preset number of neighborhood points, and obtaining feature points in the reference point cloud and the target point cloud according to the relationship between the feature indexes of the points and the feature indexes of the neighborhood points; constructing a local reference coordinate system for each feature point; and further obtaining three-dimensional local features of each feature point, matching the feature points in the reference point cloud and the target point cloud according to the three-dimensional local features to obtain multiple pairs of corresponding feature points, obtaining a three-dimensional rigid transformation matrix from the reference point cloud to the target point cloud according to the relationship between the corresponding feature points, and completing point cloud registration. According to the point cloud registration method, the influence of noise in the point cloud, isolated points, local point cloud density non-uniformity and the like on point cloud registration can be reduced, so that the point cloud registration result is accurate.

Description

technical field [0001] The invention belongs to the field of three-dimensional measurement, and more specifically relates to a point cloud registration method based on feature extraction. Background technique [0002] 3D point cloud data has the advantages of easy acquisition, simple data structure, convenient and flexible operation, and strong expression ability, and is widely used in CAD / CAM technology, reverse engineering, and parts dimensional accuracy testing and other fields. Since a picture obtained based on 3D measurement technology can only be restored to a point cloud, in order to obtain a complete point cloud model reflecting the shape of the object, it is necessary to perform a point cloud registration operation on several acquired point clouds. [0003] Coarse registration and fine registration are the main steps to complete the registration of measurement point cloud and CAD model. The rough registration process is to place the two point clouds in the same coo...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the above defects or improvement needs of the prior art, the present invention provides a point cloud registration method based on feature extraction. The corresponding feature points of the reference point cloud and the target point cloud are obtained by local features, and then the three-dimensional transformation relationship between the reference point cloud and the target point cloud is obtained, and the point cloud registration is completed. In the process, problems such as noise and isolated points in the point cloud are reduced. The influence of point cloud registration, so that the point cloud registration results are accurate

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