Topological Neighborhood Query Method of Surface Sampling Data

Abstract

The invention provides a topological neighborhood query method for sampled data on the surface of an object, which belongs to the technical field of product reverse engineering, and is characterized in that: R* tree is used to construct a dynamic spatial index for sample points on the surface of the object, and the depth-first traversal of the R* tree index is fast Obtain the k-nearest neighbor point set of the target sample point, and use it as the initial reference data of the topological neighborhood of the target sample point. According to the relationship between the neighborhood query and the sample point distribution, the kernel density estimation is used to describe the distribution law of the sample point, and the initial reference data Sampling points in the range are sorted according to their probability density, and the sampling points with the largest probability density are selected to define the local probability density maximum point, and the local probability density maximum point is used to determine the search direction, so that the initial reference data can be moderately extended to the sparse area , so as to reduce the degree of lack of neighborhood information, and iterative calculation based on this, and finally a relatively complete topological neighborhood data of the target sample point can be obtained. This method can quickly obtain the topological neighborhood data of uniform or non-uniform sampling data on complex surfaces. The query results include k-neighborhood, Voronoi neighborhood and other effective neighborhood data, which can better reflect the local type of sampling data on the surface of the object. surface features.

Description

technical field [0001] The invention provides a method for querying topological neighborhoods of sampled data on the surface of a physical object, belonging to the technical field of product reverse engineering. Background technique [0002] In reverse engineering, the surface feature analysis technology of sampled data on the physical surface is widely used to analyze the characteristic area of ​​the surface information expressed by the sampled data, and the analysis results are used as the characteristic reference data for surface modeling. The accuracy of surface feature analysis results has an important impact, and its query speed directly determines the efficiency of surface feature analysis. [0003] At present, the commonly used neighborhood data query methods include k-neighborhood query, Delaunay neighborhood query and Voronoi neighborhood query. The k-neighborhood query is currently the most widely used neighborhood query method. Based on the Euclidean distance qu...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is: to overcome the problems of low adaptability to non-uniform sampling data and low query efficiency in existing neighborhood query methods, and to provide a topological neighborhood query method for surface sampling data of real objects, which is fast, Accurately query and obtain topological neighborhood data of surface sampling data of arbitrary complex objects

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