Multi-attribute coding and dynamic weight-based graph matching method

A technology of dynamic weights and matching methods, applied in image coding, image analysis, image data processing, etc., can solve the problems of limiting the application scope of the algorithm, being stretched, the scope of application, and the lack of robustness.
CN108665490AActive Publication Date: 2018-10-16ZHEJIANG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
ZHEJIANG UNIV
Publication Date
2018-10-16

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Abstract

The invention discloses a multi-attribute coding and dynamic weight-based graph matching method. The method comprises the steps of inputting two to-be-compared graph objects and converting the graph objects into edge attribute adjacency graphs; according to information of vertexes and edges in the edge attribute adjacency graphs, performing multi-attribute coding including basic attributes and adjacency attributes for the vertexes in the edge attribute adjacency graphs; hierarchically calculating the similarity between every two vertexes in the edge attribute adjacency graphs by adopting a dynamic weight method, and performing storage to form a vertex similarity mapping matrix; and when a weighted sum of maximum weight matching of the vertex similarity mapping matrix is maximum, obtaininga similarity distance between the two graphs and corresponding edges. The basic attributes and the adjacency attributes of the edges of the graphs are comprehensively considered, and the coding and the similarity calculation are performed according to the respective characteristics, so that the stability and reliability of graph matching are improved and the application range is expanded.
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Description

technical field

[0001] The invention belongs to the field of graphic image processing, in particular to a graphic matching method based on multi-attribute coding and dynamic weight. Background technique

[0002] 3D registration refers to obtaining the accurate 3D coordinates and poses of objects in 3D space through computer graphics analysis, and binding and splicing virtual objects generated by computer into the real 3D space according to the obtained 3D coordinates to achieve the real environment and virtual objects. Accurate and seamless integration of the augmented reality system is the basis for realizing various augmented reality systems, and it is also one of the core problems to be solved.

[0003] The 3D registration method based on model keyframes needs to extract the geometric figures in the monocular image in the online stage, and match the most similar keyframe figures from the figures stored in the offline stage. However, due to the discrete processing of the ...

Claims

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