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Method for efficiently extracting public edges of large-data-volume topology-vector-free polygon

A technology with large data volume and polygons, applied in structured data retrieval, geographic information database, still image data retrieval, etc. The effect of reducing the number of cycles and improving efficiency

Pending Publication Date: 2020-01-17
SUZHOU ZHONGKE IMAGE SKY REMOTE SENSING TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0010] Aiming at the deficiencies of the prior art, the present invention provides a method for efficiently extracting the common edge of a large data volume non-topological vector polygon, which solves the problem that the extraction efficiency of the large data volume vector polygon common edge is low and cannot meet the needs of fast automatic processing

Method used

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  • Method for efficiently extracting public edges of large-data-volume topology-vector-free polygon
  • Method for efficiently extracting public edges of large-data-volume topology-vector-free polygon
  • Method for efficiently extracting public edges of large-data-volume topology-vector-free polygon

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Embodiment 1

[0045] Only adopt the synchronously increasing node method proposed in the method provided by the present invention, instead of sorting the polygons according to the order of the number of nodes contained, such as randomly extracting the common edges between adjacent polygons in the order of polygons B, C, and A:

[0046] The first step is to extract the common edges between polygon B and its adjacent polygons. The theoretical maximum number of cycles for this step is N c +N a +G bc +G ba =1007+G bc +G ba The second step is to extract the common side of polygon C and its adjacent polygons. Similarly, polygon B has been processed, and this step is no longer compared with it. Therefore, the theoretical maximum number of cycles in this step is N a +G ca =1000+G ca The third step is to extract the common side of polygon A and its adjacent polygons. Similarly, the common side of polygon B and C has been extracted, and polygon A is the last polygon. Therefore, the common side ...

Embodiment 2

[0049] The three polygons are sorted into A, B, and C according to the number of nodes contained in descending order, and then the method of synchronously adding nodes is used to extract the common edges of polygons A, B, C and their adjacent polygons: the first step is to extract The common side of polygon A and its adjacent polygons, the theoretical maximum number of cycles of this step is N b +N c +G ab +G ac =307+G ab +G ac times; the second step is to extract the common edge between polygon B and its adjacent polygons, the theoretical maximum number of cycles of this step is N c +G bc =7+G bc Second-rate;

[0050] The third step is to extract the common edge between polygon C and its adjacent polygons, which needs to be looped 0 times.

[0051] Thus, the method provided by the present invention can be used to extract all common edges between polygons A, B, and C, and the total theoretical maximum cycle is 307+G ab +G ac +7+G bc =314+G ab +G ac +G bc Second-r...

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Abstract

The invention discloses a method for efficiently extracting common edges of polygons without topological vectors in large data volume, the method comprises the step of extracting common edges of two or more polygons, and the two or more polygons are respectively provided with m nodes and m line segments and are extracted according to four steps. Compared with a traditional method, the method for extracting the common edges of the adjacent polygons is higher in efficiency and can better meet the requirement for efficiently extracting the common edges of the large-data-volume topology-vector-free polygons.

Description

technical field [0001] The invention relates to the technical field of vector data processing, in particular to a method for efficiently extracting the common side of a vector polygon with a large amount of data and no topology. Background technique [0002] Raster data and vector data are the two most basic ways of organizing spatial data in the GIS field. Among them, vector data is the basis of GIS spatial analysis application. The vectorization of raster data is the main source of vector data. However, most of the vector data generated by direct vectorization are jagged and have serious data redundancy. analysis needs. Therefore, the polygons generated by raster data vectorization usually need post-processing such as smoothing and compression. However, the polygons generated by vectorization do not contain the topological relationship between faces and edges, that is, the common edges of adjacent polygons are stored using the nodes contained in their respective polygon...

Claims

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Application Information

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IPC IPC(8): G06F16/29G06F16/56
Inventor 张亚军林巍凌刘小春王瑞瑞
Owner SUZHOU ZHONGKE IMAGE SKY REMOTE SENSING TECH CO LTD
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