Method for extracting quadric surface from three-dimensional point cloud

Abstract

The invention discloses a method for extracting a quadratic surface from a three-dimensional point cloud. The method comprises the following steps: firstly, fitting a curved surface corresponding to each point by utilizing a K neighborhood point set of each point, and calculating a curved surface parameter standard deviation corresponding to each point; arranging the point sets according to the sequence of the curved surface parameter standard deviations from small to large; sequentially taking out each point from the sequenced point set, and when the curved surface parameter standard corresponding to the taken-out point is smaller than a set threshold value and is not marked as a growing point, regarding the point as an initial seed point; carrying out region growth from the initial seedpoint, marking the growth point belonging to the curved surface by using the serial number of the current region, and carrying out dynamic fitting on the characteristic parameters of the curved surface until the growth of one curved surface is finished; and repeating the steps to take out the points from the point set and carry out dynamic fitting until the curved surface parameter standard deviation is greater than the threshold value, and finally extracting the corresponding curved surface according to the mark serial number in the point cloud. According to the method, the quadratic surfacecan be quickly and accurately extracted from the three-dimensional point cloud, and the optimal surface parameters are obtained.

Description

technical field [0001] The invention relates to the field of computer vision technology research, more particularly, to a method for extracting a quadric surface from a three-dimensional point cloud. Background technique [0002] With the development of computer technology and the continuous improvement of 3D data acquisition technology, processing 3D geometric data through computer vision has become one of the important technologies in modern manufacturing and industry. In the computer vision technology based on 3D data, point cloud is its mainstream expression form. It has the characteristics of convenient acquisition, simple data structure, and flexible expression, and is suitable for the description of large and small 3D models or 3D scenes. [0003] In the field of manufacturing and industrial production, most of its products are man-made objects designed based on CAD software, containing a large number of standard planes or quadratic surfaces, especially cylindrical su...

AI Technical Summary

Problems solved by technology

However, the current method based on region growing does not have a good solution in the selection of growth points and the formulation of growth rules. Therefore, the application of region growing in 3D point cloud data is mostly in the extraction of planes or the segmentation of smooth regions, or using the least squares method. The method of combining multiplication and region growth is used for quadratic surface extraction, but the efficiency will be greatly reduced

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