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Multilayer Riemann diagram constraint-based surface sample normal propagation method

A sample method and surface technology, applied in image enhancement, image analysis, image data processing, etc., can solve problems such as the inapplicability of the point cloud method, and achieve the effects of improving computing efficiency and accuracy, increasing throughput, and improving efficiency

Inactive Publication Date: 2018-11-23
SHANDONG UNIV OF TECH
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0004] In order to improve the situation that the existing point cloud normal estimation method is not applicable to a large number of complex surface samples, the purpose of the present invention is to propose a normal propagation method constrained by a multi-layer Riemann graph

Method used

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  • Multilayer Riemann diagram constraint-based surface sample normal propagation method
  • Multilayer Riemann diagram constraint-based surface sample normal propagation method
  • Multilayer Riemann diagram constraint-based surface sample normal propagation method

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Embodiment 1

[0033] Embodiment 1: apply the method described herein to unify the normal direction of the sampled data, wherein the normal direction is calculated by the PCA algorithm. The model has a large scale and complex structure, including sharp features, transition surfaces and other complex geometric feature areas, which can be used as model data to verify the effectiveness of the method described in this paper. By observing Figure 4 It can be seen that the method in this paper can correctly realize the normal unification of sharp features and transitional surface regions.

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Abstract

The invention aims at providing a multilayer Riemann diagram constraint-based surface sample normal propagation method suitable for mass complex sampling point set data, and belongs to the field of reverse engineering of products. The method comprises the following steps of: firstly, realizing multilayer division of surface samples by utilizing a neighborhood relationship of a target sample point,and constructing a multi-resolution model for the surface samples; secondly, constructing Riemann diagrams for nodes of the model so as to form a multilayer Riemann diagram; and finally, realizing propagation, in the multilayer Riemann diagram, of normal vectors by adoption of a top-to-bottom strategy by combining a preorder traversal algorithm and an MST algorithm. Experiment results prove thatthe method is capable of improving the normal unification correctness and remarkably improving the calculation efficiency and memory utilization rate for large-scale entity surface samples.

Description

technical field [0001] The invention provides a method for normal propagation of curved surface samples constrained by multi-layer Riemann graphs, which is suitable for massive complex curved surface samples and belongs to the field of product reverse engineering. Background technique [0002] The normal estimation of surface samples is an important problem in the surface reconstruction process. For the approximation or interpolation reconstruction of surface samples, the correctness of the reconstruction results and the computational efficiency of the reconstruction process all depend on the correct estimation results of the normal direction of the samples. For any sample point on the surface, the normal direction can be estimated based on the approximation of the local shape of the surface reflected by the position information of the sample point and its adjacent sample points. The normal direction of the sample points obtained by normal direction estimation is ambiguous,...

Claims

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Application Information

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IPC IPC(8): G06T7/50G06T17/00
CPCG06T17/00G06T2207/10028G06T7/50
Inventor 孙殿柱张硕李延瑞
Owner SHANDONG UNIV OF TECH
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